Загрузка видео...

Не удалось загрузить видео

На главную

🚀 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...

Alibaba_Qwen's profile picture

Qwen

276,586 subscribers

659,002 просмотров • 1 год назад •via X (Twitter)

Наука и технологииОбразованиеИскусство
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

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.
2:07

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 просмотров • 6 месяцев назад

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
0:43

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 просмотров • 7 месяцев назад

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:
2:09

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

413,003 просмотров • 11 месяцев назад

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):
1:12

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

126,668 просмотров • 7 месяцев назад

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.
0:42

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 просмотров • 3 лет назад

🎉 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 . 🌐
1:32

🎉 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

762,639 просмотров • 1 год назад

🚀 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
0:40

🚀 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 просмотров • 1 год назад

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:
1:39

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 просмотров • 11 месяцев назад

A few months ago Elon said progress doesn't move in a straight line. It moves in S-curves. Something breaks through, grows fast, then hits logarithmic returns and stalls until the next breakthrough. Fast forward to August 2026. xAI shipped Grok Imagine Image 2.0 on 7 August, with region-level editing and up to five reference images in one generation. It ranked second in the world on both the text-to-image and image-edit arenas. It's listed under SpaceXAI now, because SpaceX bought xAI. The Boring Company's Prufrock-2 completed a 2.28-mile Vegas Loop tunnel, its longest single drive, and moved 82,000 passengers at CONEXPO. SpaceX is going for its first orbital payload deployment on Starship Flight 14. On the 4 August earnings call Musk said that within a year they expect at least one flight a day.
1:42

A few months ago Elon said progress doesn't move in a straight line. It moves in S-curves. Something breaks through, grows fast, then hits logarithmic returns and stalls until the next breakthrough. Fast forward to August 2026. xAI shipped Grok Imagine Image 2.0 on 7 August, with region-level editing and up to five reference images in one generation. It ranked second in the world on both the text-to-image and image-edit arenas. It's listed under SpaceXAI now, because SpaceX bought xAI. The Boring Company's Prufrock-2 completed a 2.28-mile Vegas Loop tunnel, its longest single drive, and moved 82,000 passengers at CONEXPO. SpaceX is going for its first orbital payload deployment on Starship Flight 14. On the 4 August earnings call Musk said that within a year they expect at least one flight a day.

Ian Miles

39,617 просмотров • 23 дней назад

🧬 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
1:43

🧬 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

111,859 просмотров • 1 год назад

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.
5:49

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 просмотров • 10 месяцев назад

Dreamina's masterfully built next-gen AI video model serves to essentially change the game. Stepping dynamically from "clip stitching" to "long narrative × multi-asset × powerful editing" — let's review what's actually new: Seedance 2.5 is completely live worldwide on Dreamina — today — while a broader US rollout begins August 7. And yes: ✅ The entire fantastic Seedance suite (2.5, 2.0, plus all upcoming future models) is currently priced at its lowest-ever tier ✅ Dreamina obviously isn’t simply the most capable platform for Seedance 2.5 — it remains hands down the most affordable way to push it to the limits, full-capacity, requiring no add-ons ✨ 30s continuous generation (15s → 30s) — leave out the choppy stitching artifacts 📦 Up to 50 multimodal references (12 → 50) — blend your images, videos, audio, brilliantly all in one go 🎬 Precise local editing — carefully fix specific regions without ever re-rendering the whole clip 🌍 10+ languages — Spanish, Arabic, Japanese, Korean, and numerous more 🎯 3D white model & green screen support — high-level professional-grade control The fragile era of short clips is fully over. Intense industrial-grade AI video is actively here. 🚀 Coming soon on Dreamina. Meanwhile, jump in and create with Dreamina Seedance 2.5 and get your workspace ready for the upgrade! #dreamina #dreaminapartner #seedance #dreaminaseedance25
0:21

Dreamina's masterfully built next-gen AI video model serves to essentially change the game. Stepping dynamically from "clip stitching" to "long narrative × multi-asset × powerful editing" — let's review what's actually new: Seedance 2.5 is completely live worldwide on Dreamina — today — while a broader US rollout begins August 7. And yes: ✅ The entire fantastic Seedance suite (2.5, 2.0, plus all upcoming future models) is currently priced at its lowest-ever tier ✅ Dreamina obviously isn’t simply the most capable platform for Seedance 2.5 — it remains hands down the most affordable way to push it to the limits, full-capacity, requiring no add-ons ✨ 30s continuous generation (15s → 30s) — leave out the choppy stitching artifacts 📦 Up to 50 multimodal references (12 → 50) — blend your images, videos, audio, brilliantly all in one go 🎬 Precise local editing — carefully fix specific regions without ever re-rendering the whole clip 🌍 10+ languages — Spanish, Arabic, Japanese, Korean, and numerous more 🎯 3D white model & green screen support — high-level professional-grade control The fragile era of short clips is fully over. Intense industrial-grade AI video is actively here. 🚀 Coming soon on Dreamina. Meanwhile, jump in and create with Dreamina Seedance 2.5 and get your workspace ready for the upgrade! #dreamina #dreaminapartner #seedance #dreaminaseedance25

Jennifer Thompson

12,521 просмотров • 1 месяц назад

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:
1:02

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 просмотров • 7 месяцев назад

This is no routine AI‑video iteration. One model perceives scene‑level physics rather than simple pixel generation, and that is Seedance Enterprise 2.5. Creators no longer need dozens of rerolls. Most usable footage only demands 1‑2 generations, lowering overall spending and streamlining creation. It delivers AI‑free lifelike visuals, cinematic‑level lighting and camera movement, 30-second single-shot generation to orchestrate complete scene‑wide narratives. Accepts up to 50 reference inputs, so your characters and visual style stay perfectly locked across every single frame. With localized editing, the individual elements can be edited locally without re-rendering the entire video. I’ve been building a full creative pipeline on BytePlus Lumina, chaining Seedance for motion with Seedream for keyframe control and Seedaudio for adaptive soundscapes. It’s no longer about generating clips; it’s about directing scenes. Seedance 2.5 API is about to launch on BytePlus, and now you can try it directly on Lumina.
0:30

This is no routine AI‑video iteration. One model perceives scene‑level physics rather than simple pixel generation, and that is Seedance Enterprise 2.5. Creators no longer need dozens of rerolls. Most usable footage only demands 1‑2 generations, lowering overall spending and streamlining creation. It delivers AI‑free lifelike visuals, cinematic‑level lighting and camera movement, 30-second single-shot generation to orchestrate complete scene‑wide narratives. Accepts up to 50 reference inputs, so your characters and visual style stay perfectly locked across every single frame. With localized editing, the individual elements can be edited locally without re-rendering the entire video. I’ve been building a full creative pipeline on BytePlus Lumina, chaining Seedance for motion with Seedream for keyframe control and Seedaudio for adaptive soundscapes. It’s no longer about generating clips; it’s about directing scenes. Seedance 2.5 API is about to launch on BytePlus, and now you can try it directly on Lumina.

SANI BULA

174,790 просмотров • 26 дней назад

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
0:28

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 просмотров • 11 месяцев назад