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🚀 Excited to introduce Qwen-Image-Edit! Built on 20B Qwen-Image, it brings precise bilingual text editing (Chinese & English) while preserving style, and supports both semantic and appearance-level editing. ✨ Key Features ✅ Accurate text editing with bilingual support ✅ High-level semantic editing (e.g. object rotation, IP creation) ✅ Low-level... show more

Qwen

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658,347 Aufrufe • vor 11 Monaten •via X (Twitter)

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Meet Qwen-Image-Edit, your smart, seamless image editing companion! Built on the powerful 20B Qwen-Image model, it handles both visual and semantic edits, and delivers state-of-the-art performance. Whether you're refining visuals or transforming styles, it’s got you covered! ✨

Meet Qwen-Image-Edit, your smart, seamless image editing companion! Built on the powerful 20B Qwen-Image model, it handles both visual and semantic edits, and delivers state-of-the-art performance. Whether you're refining visuals or transforming styles, it’s got you covered! ✨

Alibaba Group

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1/4 🚀We are launching Qwen-Image-2.0, a next-generation foundational image generation model. The key highlights of Qwen-Image-2.0 include: Professional Typography Rendering: Supports 1k-token instructions for direct generation of professional infographics, including PPTs, posters, comics, and more. Stronger Semantic Adherence: Native 2K resolution support for finely detailed realistic scenes, including people, nature, and architecture. Improved Text Rendering: Integrated understanding and generation capabilities, unifying image generation and editing in a single mode Lighter Model Architecture: Smaller model size with faster inference speed.

1/4 🚀We are launching Qwen-Image-2.0, a next-generation foundational image generation model. The key highlights of Qwen-Image-2.0 include: Professional Typography Rendering: Supports 1k-token instructions for direct generation of professional infographics, including PPTs, posters, comics, and more. Stronger Semantic Adherence: Native 2K resolution support for finely detailed realistic scenes, including people, nature, and architecture. Improved Text Rendering: Integrated understanding and generation capabilities, unifying image generation and editing in a single mode Lighter Model Architecture: Smaller model size with faster inference speed.

Tongyi Lab

164,097 Aufrufe • vor 5 Monaten

Grok Imagine API now supports built-in video editing on top of powerful video generation You can feed in your own videos and edit them directly with Grok Imagine, transforming or enhancing footage without traditional timeline editing Developers can generate high-quality videos at scale with fast iteration and simple integration into existing workflows One API does it all: • Text-to-video • Image-to-video • Edit existing videos directly • Replace, remove, or add objects inside a video • Built-in audio sync for every clip Turn your ideas into finished videos – at scale, through a single API

Grok Imagine API now supports built-in video editing on top of powerful video generation You can feed in your own videos and edit them directly with Grok Imagine, transforming or enhancing footage without traditional timeline editing Developers can generate high-quality videos at scale with fast iteration and simple integration into existing workflows One API does it all: • Text-to-video • Image-to-video • Edit existing videos directly • Replace, remove, or add objects inside a video • Built-in audio sync for every clip Turn your ideas into finished videos – at scale, through a single API

X Freeze

19,054 Aufrufe • vor 5 Monaten

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

We’re excited to announce the release and open-source of HunyuanImage 3.0 — the largest and most powerful open-source text-to-image model to date, with over 80 billion total parameters, of which 13 billion are activated per token during inference.The effect is completely comparable to the industry’s flagship closed-source model.🚀🚀🚀 HunyuanImage 3.0 originates from our internally developed native multimodal large language model, with fine-tuning and post-training focused on text-to-image generation. This unique foundation gives the model a powerful set of capabilities: ✅Reason with world knowledge ✅Understand complex, thousand-word prompts ✅Generate precise text within images Different from traditional DiT architecture image generation models, HunyuanImage 3.0’s MoE architecture uses a Transfusion-based approach to deeply couple Diffusion and LLM training for a single, powerful system. Built on Hunyuan-A13B, HunyuanImage 3.0 was trained on a massive dataset: 5 billion image-text pairs, video frames, interleaved image-text data, and 6 trillion tokens of text corpora. This hybrid training across multimodal generation, understanding, and LLM capabilities allows the model to seamlessly integrate multiple tasks. Whether you're an illustrator, designer, or creator, this is built to slash your workflow from hours to minutes. HunyuanImage 3.0 can generate intricate text, detailed comics, expressive emojis, and lively, engaging illustrations for educational content. The current release focuses solely on text-to-image generation and future updates will include image-to-image, image editing, multi-turn interaction, and more. 👉🏻Try it now: 🔗GitHub: 🤗Hugging Face:

Tencent Hy

412,658 Aufrufe • vor 9 Monaten

Leonardo’s Omni Editing is here — powered by FLUX.1 Kontext and GPT-Image-1 You can now edit any image right inside the viewer — with a simple prompt. No switching tools. No breaking flow. This launch is powered by two advanced Omni models: ✅ GPT-Image-1 — for multi-reference creativity and context-aware generation ✅ FLUX.1 Kontext — developed by Black Forest Labs, with Leonardo as an official launch partner. Built for fast, controlled edits that preserve key details. What’s new: • Inline prompt bar built into every generated image • Make fast, precise edits: lighting, objects, layout, even in-image text • Switch between models based on your creative needs • Stay in one workflow — no extra steps, no restarts Try it now 🔥

Leonardo’s Omni Editing is here — powered by FLUX.1 Kontext and GPT-Image-1 You can now edit any image right inside the viewer — with a simple prompt. No switching tools. No breaking flow. This launch is powered by two advanced Omni models: ✅ GPT-Image-1 — for multi-reference creativity and context-aware generation ✅ FLUX.1 Kontext — developed by Black Forest Labs, with Leonardo as an official launch partner. Built for fast, controlled edits that preserve key details. What’s new: • Inline prompt bar built into every generated image • Make fast, precise edits: lighting, objects, layout, even in-image text • Switch between models based on your creative needs • Stay in one workflow — no extra steps, no restarts Try it now 🔥

Leonardo.Ai

33,908 Aufrufe • vor 1 Jahr

Today, we introduce HunyuanImage 3.0-Instruct, a native multimodal model focusing on image-editing by integrating visual understanding with precise image synthesis! 🚀 It understands input images and reasons before generating images. Built on an 80B-parameter MoE architecture (13B activated), it natively unifies deep multimodal comprehension and high-fidelity generation. 🧠 A "Thinking" Model with Native CoT & MixGRPO: The model doesn’t just execute commands, it processes them through a Native Chain-of-Thought (CoT) schema. Enhanced by our self-developed MixGRPO algorithm, it reasons through complex instructions to achieve flawless intent alignment and human-preference consistency. 🎨 Precise Editing & Multi-Image Fusion: The model enables accurate image editing by adding, removing, or modifying elements while keeping non-target areas perfectly intact. It also excels at seamless multi-image fusion, synthesizing complex scenes by extracting and blending elements from multiple sources into a unified, consistent output. 🏆 SOTA Performance: HunyuanImage 3.0-Instruct sets a new benchmark in visual quality and alignment, delivering performance that matches leading proprietary models. We aim to enable the community to explore new ideas with a state-of-the-art foundation model, fostering a dynamic and vibrant image generation ecosystem. 🛠️🎨 💻Try it at (PC only):

Today, we introduce HunyuanImage 3.0-Instruct, a native multimodal model focusing on image-editing by integrating visual understanding with precise image synthesis! 🚀 It understands input images and reasons before generating images. Built on an 80B-parameter MoE architecture (13B activated), it natively unifies deep multimodal comprehension and high-fidelity generation. 🧠 A "Thinking" Model with Native CoT & MixGRPO: The model doesn’t just execute commands, it processes them through a Native Chain-of-Thought (CoT) schema. Enhanced by our self-developed MixGRPO algorithm, it reasons through complex instructions to achieve flawless intent alignment and human-preference consistency. 🎨 Precise Editing & Multi-Image Fusion: The model enables accurate image editing by adding, removing, or modifying elements while keeping non-target areas perfectly intact. It also excels at seamless multi-image fusion, synthesizing complex scenes by extracting and blending elements from multiple sources into a unified, consistent output. 🏆 SOTA Performance: HunyuanImage 3.0-Instruct sets a new benchmark in visual quality and alignment, delivering performance that matches leading proprietary models. We aim to enable the community to explore new ideas with a state-of-the-art foundation model, fostering a dynamic and vibrant image generation ecosystem. 🛠️🎨 💻Try it at (PC only):

Tencent Hy

125,803 Aufrufe • vor 5 Monaten

🎉 恭喜发财🧧🐍 As we welcome the Chinese New Year, we're thrilled to announce the launch of Qwen2.5-VL , our latest flagship vision-language model! 🚀 💗 Qwen Chat: 📖 Blog: 🤗 Hugging Face: 🤖 ModelScope: 🌟 Key Highlights: * Visual Understanding : From flowers to complex charts, Qwen2.5-VL sees it all! * Agentic Capabilities : It’s a visual agent that can reason and interact with tools like computers & phones. * Long Video Comprehension : Captures events in videos over 1 hour long! ⏳🎥 * Precise Localization : Generates bounding boxes & JSON outputs for accurate object detection. * Structured Data Outputs : Perfect for finance & commerce, handling invoices, forms & more! 💼📊 Try Qwen2.5-VL now at Qwen Chat or explore models on Hugging Face & ModelScope . 🌐

🎉 恭喜发财🧧🐍 As we welcome the Chinese New Year, we're thrilled to announce the launch of Qwen2.5-VL , our latest flagship vision-language model! 🚀 💗 Qwen Chat: 📖 Blog: 🤗 Hugging Face: 🤖 ModelScope: 🌟 Key Highlights: * Visual Understanding : From flowers to complex charts, Qwen2.5-VL sees it all! * Agentic Capabilities : It’s a visual agent that can reason and interact with tools like computers & phones. * Long Video Comprehension : Captures events in videos over 1 hour long! ⏳🎥 * Precise Localization : Generates bounding boxes & JSON outputs for accurate object detection. * Structured Data Outputs : Perfect for finance & commerce, handling invoices, forms & more! 💼📊 Try Qwen2.5-VL now at Qwen Chat or explore models on Hugging Face & ModelScope . 🌐

Qwen

762,314 Aufrufe • vor 1 Jahr

Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields paper page: Editing a local region or a specific object in a 3D scene represented by a NeRF is challenging, mainly due to the implicit nature of the scene representation. Consistently blending a new realistic object into the scene adds an additional level of difficulty. We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts or image patches, along with a 3D ROI box. Our method leverages a pretrained language-image model to steer the synthesis towards a user-provided text prompt or image patch, along with a 3D MLP model initialized on an existing NeRF scene to generate the object and blend it into a specified region in the original scene. We allow local editing by localizing a 3D ROI box in the input scene, and seamlessly blend the content synthesized inside the ROI with the existing scene using a novel volumetric blending technique. To obtain natural looking and view-consistent results, we leverage existing and new geometric priors and 3D augmentations for improving the visual fidelity of the final result. We test our framework both qualitatively and quantitatively on a variety of real 3D scenes and text prompts, demonstrating realistic multi-view consistent results with much flexibility and diversity compared to the baselines. Finally, we show the applicability of our framework for several 3D editing applications, including adding new objects to a scene, removing/replacing/altering existing objects, and texture conversion.

Blended-NeRF: Zero-Shot Object Generation and Blending in Existing Neural Radiance Fields paper page: Editing a local region or a specific object in a 3D scene represented by a NeRF is challenging, mainly due to the implicit nature of the scene representation. Consistently blending a new realistic object into the scene adds an additional level of difficulty. We present Blended-NeRF, a robust and flexible framework for editing a specific region of interest in an existing NeRF scene, based on text prompts or image patches, along with a 3D ROI box. Our method leverages a pretrained language-image model to steer the synthesis towards a user-provided text prompt or image patch, along with a 3D MLP model initialized on an existing NeRF scene to generate the object and blend it into a specified region in the original scene. We allow local editing by localizing a 3D ROI box in the input scene, and seamlessly blend the content synthesized inside the ROI with the existing scene using a novel volumetric blending technique. To obtain natural looking and view-consistent results, we leverage existing and new geometric priors and 3D augmentations for improving the visual fidelity of the final result. We test our framework both qualitatively and quantitatively on a variety of real 3D scenes and text prompts, demonstrating realistic multi-view consistent results with much flexibility and diversity compared to the baselines. Finally, we show the applicability of our framework for several 3D editing applications, including adding new objects to a scene, removing/replacing/altering existing objects, and texture conversion.

AK

62,768 Aufrufe • vor 3 Jahren

🚀 Introducing HunyuanCustom: An open-source, multimodal-driven architecture for customized video generation, powered by HunyuanVideo-13B. Outperforming existing open-source models, it rivals top closed-source solutions! 🎥 Highlights: ✅Subject Consistency: Maintains identity across single & multi-subject video generation. ✅Multimodal Inputs: Supports text, images, audio, and video for highly controlled outputs. ✅High-Quality Output: Industry-leading detail, motion smoothness, and lighting realism. Key Features: 1️⃣Single-Subject Video: Upload an image + text (e.g., “He’s walking a dog”) to create coherent videos with new actions, outfits, and scenes. 2️⃣Multi-Subject Video: Generate videos with multiple subjects (e.g., a man drinking coffee in a cozy room) from separate image inputs. 3️⃣Audio-Driven Video: Sync audio with visuals for talking or singing in any scene—perfect for digital avatars, virtual customer service, and more. 4️⃣Video-Driven Video: Seamlessly insert or replace subjects into any video for creative enhancements. Dive Deeper: 🌐Project: 📝Technical Details: 💻Code: The single-subject video capability is open-sourced and live on the Hunyuan website, with more features to be released soon! 👉 Try it now: #HunyuanCustom #VideoGeneration #AI #TencentHunyuan

🚀 Introducing HunyuanCustom: An open-source, multimodal-driven architecture for customized video generation, powered by HunyuanVideo-13B. Outperforming existing open-source models, it rivals top closed-source solutions! 🎥 Highlights: ✅Subject Consistency: Maintains identity across single & multi-subject video generation. ✅Multimodal Inputs: Supports text, images, audio, and video for highly controlled outputs. ✅High-Quality Output: Industry-leading detail, motion smoothness, and lighting realism. Key Features: 1️⃣Single-Subject Video: Upload an image + text (e.g., “He’s walking a dog”) to create coherent videos with new actions, outfits, and scenes. 2️⃣Multi-Subject Video: Generate videos with multiple subjects (e.g., a man drinking coffee in a cozy room) from separate image inputs. 3️⃣Audio-Driven Video: Sync audio with visuals for talking or singing in any scene—perfect for digital avatars, virtual customer service, and more. 4️⃣Video-Driven Video: Seamlessly insert or replace subjects into any video for creative enhancements. Dive Deeper: 🌐Project: 📝Technical Details: 💻Code: The single-subject video capability is open-sourced and live on the Hunyuan website, with more features to be released soon! 👉 Try it now: #HunyuanCustom #VideoGeneration #AI #TencentHunyuan

Tencent HY

191,908 Aufrufe • vor 1 Jahr

We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

Tencent Hy

89,257 Aufrufe • vor 10 Monaten

🧬 BREAKING: Our CRISPR-GPT paper is out TODAY in Nature Biomedical Engineering Nature Biomedical Engineering ! 🤯 We built an AI agent that turns ANYONE into a gene-editing expert in 1 DAY instead of months. An undergrad with ZERO experience achieved 90%+ editing efficiency on their FIRST attempt. 🧵 Here's how we're building expert AI agents for cutting-edge biotechnology: 🎯 The Problem: CRISPR is revolutionary but requires PhD-level expertise, it can take weeks to learn, adopt, and design, analyze a CRISPR experiment for R&D or making life-saving medicine. Even Pro scientists can make small mistakes (e.g. typos in guideRNA or cloning design) that cost months to find out, slowing us down. 💡 Our Solution: CRISPR-GPT - an AI co-pilot from Stanford University Princeton University Google DeepMind that guides you through EVERY step via simple conversation 🔬 Real Results: -Novice researcher: ~90% editing on 1st go -Training time: Months → 1 day -100% success rate in our trials -Even experts save days/weeks on data analysis & troubleshooting 🤖 How it works: Our multi-agent system handles: CRISPR system and delivery method selection, guideRNA design, Protocol generation, Real-time troubleshooting, Data analysis, and beyond. All through natural language! No coding, no complex software. 📊 We benchmarked it extensively: -288 evaluation scenarios/cases -Outperformed GPT-4o on ALL gene editing tasks -Trained on 11 years of expert discussions -Covers knockout, base-editing, prime-editing & epigenetic editing 🌍 Why this matters: -Every lab can now use CRISPR with an AI system distilling expert knowledge and skills. -Every student can learn faster. -Every researcher can tackle bigger challenges without worrying about small mistakes. -Customized CRISPR design can be automated based on your need and the context of R&D workflow. -Agentic AI ensure safety, privacy, and responsibility -We're not just automating gene editing - we're using AI to power scientists to cure diseases. 🚀 Try it yourself! Beta access available at: Paper: Code: Benchmark (companion work, Genome-bench): Co-first and key authors: Yuanhao Qu Kaixuan Huang Ming Yin PIs: Le Cong@Stanford, AI+Bio+Gene-Editing Mengdi Wang Key collaborators: Russ Altman Denny Zhou The future of biology and science is conversational. The future is now. Nature Biomedical Engineering Nature Portfolio #CRISPR #AI #GeneEditing #Biotech #Science #AISafety

🧬 BREAKING: Our CRISPR-GPT paper is out TODAY in Nature Biomedical Engineering Nature Biomedical Engineering ! 🤯 We built an AI agent that turns ANYONE into a gene-editing expert in 1 DAY instead of months. An undergrad with ZERO experience achieved 90%+ editing efficiency on their FIRST attempt. 🧵 Here's how we're building expert AI agents for cutting-edge biotechnology: 🎯 The Problem: CRISPR is revolutionary but requires PhD-level expertise, it can take weeks to learn, adopt, and design, analyze a CRISPR experiment for R&D or making life-saving medicine. Even Pro scientists can make small mistakes (e.g. typos in guideRNA or cloning design) that cost months to find out, slowing us down. 💡 Our Solution: CRISPR-GPT - an AI co-pilot from Stanford University Princeton University Google DeepMind that guides you through EVERY step via simple conversation 🔬 Real Results: -Novice researcher: ~90% editing on 1st go -Training time: Months → 1 day -100% success rate in our trials -Even experts save days/weeks on data analysis & troubleshooting 🤖 How it works: Our multi-agent system handles: CRISPR system and delivery method selection, guideRNA design, Protocol generation, Real-time troubleshooting, Data analysis, and beyond. All through natural language! No coding, no complex software. 📊 We benchmarked it extensively: -288 evaluation scenarios/cases -Outperformed GPT-4o on ALL gene editing tasks -Trained on 11 years of expert discussions -Covers knockout, base-editing, prime-editing & epigenetic editing 🌍 Why this matters: -Every lab can now use CRISPR with an AI system distilling expert knowledge and skills. -Every student can learn faster. -Every researcher can tackle bigger challenges without worrying about small mistakes. -Customized CRISPR design can be automated based on your need and the context of R&D workflow. -Agentic AI ensure safety, privacy, and responsibility -We're not just automating gene editing - we're using AI to power scientists to cure diseases. 🚀 Try it yourself! Beta access available at: Paper: Code: Benchmark (companion work, Genome-bench): Co-first and key authors: Yuanhao Qu Kaixuan Huang Ming Yin PIs: Le Cong@Stanford, AI+Bio+Gene-Editing Mengdi Wang Key collaborators: Russ Altman Denny Zhou The future of biology and science is conversational. The future is now. Nature Biomedical Engineering Nature Portfolio #CRISPR #AI #GeneEditing #Biotech #Science #AISafety

Le Cong@Stanford, AI+Bio+Gene-Editing

111,784 Aufrufe • vor 11 Monaten

AgiBot Launches 'LinkCraft' Platform: Zero-Code Motion Creation for Humanoid Robots On October 24, 2025, AgiBot introduced its "LinkCraft" platform, a zero-code, zero-barrier system for creating humanoid robot content. The platform integrates AI motion capture, cloud-based imitation learning, and multimodal choreography capabilities. The core feature allows users to upload a video of human performance, and the platform automatically converts it into precise robot control strategies using AI vision and smart redirection—no programming required. This includes future support for finger-level fine manipulation. LinkCraft also features "Speech Choreography," which generates corresponding robot gestures and expressions based on semantic analysis of uploaded text or audio, offering customizable voice and emotion settings. For complex performances, the platform provides "storyline" tools, enabling users to combine multiple actions, voices, and expressions on a timeline, similar to video editing software. Furthermore, it supports multi-robot group control and access to an official library of over 180 actions for rapid content creation. The platform is currently adapted for the AgiBot X2 and aims to increase the accessibility and application scale of humanoid robots.

AgiBot Launches 'LinkCraft' Platform: Zero-Code Motion Creation for Humanoid Robots On October 24, 2025, AgiBot introduced its "LinkCraft" platform, a zero-code, zero-barrier system for creating humanoid robot content. The platform integrates AI motion capture, cloud-based imitation learning, and multimodal choreography capabilities. The core feature allows users to upload a video of human performance, and the platform automatically converts it into precise robot control strategies using AI vision and smart redirection—no programming required. This includes future support for finger-level fine manipulation. LinkCraft also features "Speech Choreography," which generates corresponding robot gestures and expressions based on semantic analysis of uploaded text or audio, offering customizable voice and emotion settings. For complex performances, the platform provides "storyline" tools, enabling users to combine multiple actions, voices, and expressions on a timeline, similar to video editing software. Furthermore, it supports multi-robot group control and access to an official library of over 180 actions for rapid content creation. The platform is currently adapted for the AgiBot X2 and aims to increase the accessibility and application scale of humanoid robots.

RoboHub🤖

21,679 Aufrufe • vor 8 Monaten

Turn Any Song Into a Fresh Instrumental in Just a Few Clicks If you're a content creator, editor, or music enthusiast, you know how hard it is to find background tracks that truly match your style. That’s where Mureka AI comes in. Upload a track you like from your device or a YouTube link, and Mureka will generate a brand new instrumental that captures a similar vibe. No plugins. No editing skills. Just fast, high-quality output ready to use. Here’s how it works: 1. Upload any track with vocals from your device or YouTube 2. Pick a music scenario and mood 3. Click Done — Mureka handles the rest 4. Preview and download your custom instrumental The result is a clean, demo-level track that feels polished and personal. ✅ Mureka uses your reference to match the style ✅ Great for beat demos, background music, or creative projects ✅ Built for speed and made to sound good Perfect for monetization, music creation, or powering your content channel. Whether you’re editing a reel, building a beat pack, or just need fresh sound quickly, Mureka makes it simple. Make your content sound original: #MurekaAI #InstrumentalMusic #MusicForCreators #AIMusic

Markandey Sharma

94,526 Aufrufe • vor 1 Jahr

Big news X-Design just released a brand-new version with even more powerful features for product photo creation. If you sell on platforms like Etsy or run your own store, this is seriously worth checking out: ✅ Auto-Generated Product Listing Sets: Upload one product photo, and X-Design instantly creates a full set - main image, lifestyle scene, hand-held, and detail shot. No extra editing apps needed. ✅ Lifestyle-Focused AI Background Generator: Replace plain backdrops with cozy, natural home scenes that feel warm and real - perfect for home decor, candles, fashion, and more. ✅ AI Model Try-On (for T-shirt POD sellers): Turn flat product images into professional model shots with one click, choosing from different model styles to match your brand. ✅ All-in-One Photo Editor Workflow: Background Removal with clean edges Object Eraser to remove distractions Product Retouching to polish surface details Clarity Enhancer for sharper, clearer product images ✅ Candle Lit Effect: X-Design auto-lights candles in product scenes so buyers can instantly visualize how it looks when lit.

ghotai غوټی

92,790 Aufrufe • vor 1 Jahr

Meet Tencent HY 3D Studio 1.2 👋 With this major upgrade to our 3D creation pipeline, you can generate assets with sculpt-level detail and fine-grained interactive control. Starting today, the studio is officially open for Public Beta — no application required. Tencent HY 3D Studio 1.2 introduces a suite of features built for creative precision, including: 🧩 PartGen 1.5: High-Precision Component Partitioning — 1536³ Resolution: Boosted from 1024³ for crystal-clear model splitting and ultra-fine detail retention. — Fine-Grained Interaction: Introducing intuitive, brush-based control for precise, manual component editing. — Shape Adherence: Drastically improved geometry integrity for even the most intricate objects. 🎨 Tencent HY 3D 3.1: Sculpt-Level Detail — Enhanced Geometry: Fine-grained details that adapt perfectly to stylized inputs.. — Texture Fidelity: A massive leap in color accuracy and texture fidelity, reflecting your original input with stunning realism. — 8-View Control: Expanded from 4 to 8 input views for ultimate reconstruction accuracy. ✨We’re so excited to see what you create! Try it now:

Meet Tencent HY 3D Studio 1.2 👋 With this major upgrade to our 3D creation pipeline, you can generate assets with sculpt-level detail and fine-grained interactive control. Starting today, the studio is officially open for Public Beta — no application required. Tencent HY 3D Studio 1.2 introduces a suite of features built for creative precision, including: 🧩 PartGen 1.5: High-Precision Component Partitioning — 1536³ Resolution: Boosted from 1024³ for crystal-clear model splitting and ultra-fine detail retention. — Fine-Grained Interaction: Introducing intuitive, brush-based control for precise, manual component editing. — Shape Adherence: Drastically improved geometry integrity for even the most intricate objects. 🎨 Tencent HY 3D 3.1: Sculpt-Level Detail — Enhanced Geometry: Fine-grained details that adapt perfectly to stylized inputs.. — Texture Fidelity: A massive leap in color accuracy and texture fidelity, reflecting your original input with stunning realism. — 8-View Control: Expanded from 4 to 8 input views for ultimate reconstruction accuracy. ✨We’re so excited to see what you create! Try it now:

Tencent Hy

83,314 Aufrufe • vor 6 Monaten

🇨🇳 Another great Chinese Model, OmniHuman-1.5 from ByteDance Turns 1 image plus a voice track into expressive avatar video by pairing a System 1 and System 2 inspired planner with a Diffusion Transformer, Produces coherent motion for over 1 minute with moving camera and multi character scenes. Most avatar models move to the beat of the audio but miss meaning, so gestures feel generic and emotions feel shallow. The fix here is a Multimodal LLM planner that listens to the speech and drafts a structured plan describing intent, emotions, beats, and high level actions, which gives the motion engine clear semantic targets instead of only rhythm. The motion engine is a Multimodal Diffusion Transformer that fuses the plan with audio, the single reference image, and optional text prompts, then synthesizes continuous body, face, and head motion that matches both words and tone. A key trick is a Pseudo Last Frame, a synthetic target that summarizes the next expected state, which stabilizes fusion across modalities and keeps motion consistent over long spans. From just 1 image and speech, the system outputs speaking avatars with synchronized lips, context aware gestures, and continuous camera movement, and it also supports multi character interactions without manual choreography. Reported results show strong lip sync accuracy, high video quality, natural motion, and close match to text prompts, and the same setup works on nonhuman characters too.

Rohan Paul

63,859 Aufrufe • vor 10 Monaten

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld

Tencent HY

20,178 Aufrufe • vor 10 Monaten

✨"Cubism Editor 5.4.00 alpha1" limited release until September 14, 2026✨ We are also releasing Cubism 5 SDK for Unity R7 alpha1, which supports these new features, at the same time. Check out the accompanying digest video to learn about the main new features. 🔥[New Features] ✏️ [Parameter Controller SDK Support] Parameter controllers (IK) are now supported in the SDK. You can configure them directly on the model and export them as runtime files. Additionally, a new "target-only" controller can be defined to allow the controller to follow a path. ✏️ [Model State Set] A new model state set feature has been added. You can register working states in a dedicated palette, enabling you to recall specific states of visibility, lock, and parameter values with a single click. This helps you work more efficiently by allowing you to switch between states tailored to different tasks. ✏️[Expanded Editing Support for External Application Integration API ] The external application integration API has been expanded to include object editing and more. You can now integrate an API to directly add and edit parts, deformers, and parameters on models in the editor. ✏️[Enhanced automatic layout for texture atlases] The automatic layout algorithm for texture atlas editing has been completely redesigned. This enables more efficient packing with less unused space. You can configure the layout settings individually for each texture, allowing for flexible layouts. [How to use Cubism 5.4 alpha] Please see the announcement page for details on downloading and feedback. ⚠Notes on using the alpha version - The alpha version is provided for the purpose of gathering feedback on the usability and performance of new features. - Usage Period: Until September 14, 2026. - Please be sure to create a backup, as there is a possibility of data corruption. - Alpha version data and SDK outputs are not guaranteed to function properly and we do not provide support for it. #Live2D #cubism54_alpha

✨"Cubism Editor 5.4.00 alpha1" limited release until September 14, 2026✨ We are also releasing Cubism 5 SDK for Unity R7 alpha1, which supports these new features, at the same time. Check out the accompanying digest video to learn about the main new features. 🔥[New Features] ✏️ [Parameter Controller SDK Support] Parameter controllers (IK) are now supported in the SDK. You can configure them directly on the model and export them as runtime files. Additionally, a new "target-only" controller can be defined to allow the controller to follow a path. ✏️ [Model State Set] A new model state set feature has been added. You can register working states in a dedicated palette, enabling you to recall specific states of visibility, lock, and parameter values with a single click. This helps you work more efficiently by allowing you to switch between states tailored to different tasks. ✏️[Expanded Editing Support for External Application Integration API ] The external application integration API has been expanded to include object editing and more. You can now integrate an API to directly add and edit parts, deformers, and parameters on models in the editor. ✏️[Enhanced automatic layout for texture atlases] The automatic layout algorithm for texture atlas editing has been completely redesigned. This enables more efficient packing with less unused space. You can configure the layout settings individually for each texture, allowing for flexible layouts. [How to use Cubism 5.4 alpha] Please see the announcement page for details on downloading and feedback. ⚠Notes on using the alpha version - The alpha version is provided for the purpose of gathering feedback on the usability and performance of new features. - Usage Period: Until September 14, 2026. - Please be sure to create a backup, as there is a possibility of data corruption. - Alpha version data and SDK outputs are not guaranteed to function properly and we do not provide support for it. #Live2D #cubism54_alpha

Live2D

70,544 Aufrufe • vor 1 Tag

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale blog: Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity text or image outputs, but are also generalists which can solve tasks not explicitly taught. In contrast, speech generative models are still primitive in terms of scale and task generalization. In this paper, we present Voicebox, the most versatile text-guided generative model for speech at scale. Voicebox is a non-autoregressive flow-matching model trained to infill speech, given audio context and text, trained on over 50K hours of speech that are neither filtered nor enhanced. Similar to GPT, Voicebox can perform many different tasks through in-context learning, but is more flexible as it can also condition on future context. Voicebox can be used for mono or cross-lingual zero-shot text-to-speech synthesis, noise removal, content editing, style conversion, and diverse sample generation. In particular, Voicebox outperforms the state-of-the-art zero-shot TTS model VALL-E on both intelligibility (5.9% vs 1.9% word error rates) and audio similarity (0.580 vs 0.681) while being up to 20 times faster.

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale blog: Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity text or image outputs, but are also generalists which can solve tasks not explicitly taught. In contrast, speech generative models are still primitive in terms of scale and task generalization. In this paper, we present Voicebox, the most versatile text-guided generative model for speech at scale. Voicebox is a non-autoregressive flow-matching model trained to infill speech, given audio context and text, trained on over 50K hours of speech that are neither filtered nor enhanced. Similar to GPT, Voicebox can perform many different tasks through in-context learning, but is more flexible as it can also condition on future context. Voicebox can be used for mono or cross-lingual zero-shot text-to-speech synthesis, noise removal, content editing, style conversion, and diverse sample generation. In particular, Voicebox outperforms the state-of-the-art zero-shot TTS model VALL-E on both intelligibility (5.9% vs 1.9% word error rates) and audio similarity (0.580 vs 0.681) while being up to 20 times faster.

AK

429,307 Aufrufe • vor 3 Jahren

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date. Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike. More details and examples of what Movie Gen can do ➡️ 🛠️ Movie Gen models and capabilities Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt. Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment. Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes. Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video. We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date. Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike. More details and examples of what Movie Gen can do ➡️ 🛠️ Movie Gen models and capabilities Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt. Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment. Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes. Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video. We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

AI at Meta

2,264,759 Aufrufe • vor 1 Jahr