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Zero-shot video reasoning (chain-of-frames) isn’t just for Veo3 — open-source models can understand and edit too! 🕹️ ChronoEdit brings temporal reasoning to image editing. 🔗

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Xuanchi Ren

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22,661 görüntüleme • 10 ay önce •via X (Twitter)

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Introduce CoT-VLA – Visual Chain-of-Thought reasoning for Robot Foundation Models! 🤖 By leveraging next-frame prediction as visual chain-of-thought reasoning, CoT-VLA uses future prediction to guide action generation and unlock large-scale video data for training. #CVPR2025

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Image generation with Gemini just got a bananas upgrade and is the new state-of-the-art image generation and editing model. 🤯 From photorealistic masterpieces to mind-bending fantasy worlds, you can now natively produce, edit and refine visuals with new levels of reasoning, control and creativity. A quick dive into Gemini 2.5 Flash’s capabilities 🧵
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Image generation with Gemini just got a bananas upgrade and is the new state-of-the-art image generation and editing model. 🤯 From photorealistic masterpieces to mind-bending fantasy worlds, you can now natively produce, edit and refine visuals with new levels of reasoning, control and creativity. A quick dive into Gemini 2.5 Flash’s capabilities 🧵

Google DeepMind

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My favorite paper this year: "Video models are zero-shot learners and reasoners" It illustrates that video models show emergent visual reasoning at scale - they can solve vision tasks they weren't trained for. This may be the "GPT moment" for vision. Let's break it down 👇
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My favorite paper this year: "Video models are zero-shot learners and reasoners" It illustrates that video models show emergent visual reasoning at scale - they can solve vision tasks they weren't trained for. This may be the "GPT moment" for vision. Let's break it down 👇

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185,286 görüntüleme • 7 ay önce

"SAM2Matting: Generalized Image and Video Matting" TL;DR: upgrades foundation video trackers like SAM2 into state-of-the-art image and video matting models by decoupling temporal tracking from fine-grained alpha estimation achieving zero-shot video matting without video training
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"SAM2Matting: Generalized Image and Video Matting" TL;DR: upgrades foundation video trackers like SAM2 into state-of-the-art image and video matting models by decoupling temporal tracking from fine-grained alpha estimation achieving zero-shot video matting without video training

Alexandre Morgand

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Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation paper page: Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable challenge. This paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts: key frame translation and full video translation. The first part uses an adapted diffusion model to generate key frames, with hierarchical cross-frame constraints applied to enforce coherence in shapes, textures and colors. The second part propagates the key frames to other frames with temporal-aware patch matching and frame blending. Our framework achieves global style and local texture temporal consistency at a low cost (without re-training or optimization). The adaptation is compatible with existing image diffusion techniques, allowing our framework to take advantage of them, such as customizing a specific subject with LoRA, and introducing extra spatial guidance with ControlNet. Extensive experimental results demonstrate the effectiveness of our proposed framework over existing methods in rendering high-quality and temporally-coherent videos.
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Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation paper page: Large text-to-image diffusion models have exhibited impressive proficiency in generating high-quality images. However, when applying these models to video domain, ensuring temporal consistency across video frames remains a formidable challenge. This paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts: key frame translation and full video translation. The first part uses an adapted diffusion model to generate key frames, with hierarchical cross-frame constraints applied to enforce coherence in shapes, textures and colors. The second part propagates the key frames to other frames with temporal-aware patch matching and frame blending. Our framework achieves global style and local texture temporal consistency at a low cost (without re-training or optimization). The adaptation is compatible with existing image diffusion techniques, allowing our framework to take advantage of them, such as customizing a specific subject with LoRA, and introducing extra spatial guidance with ControlNet. Extensive experimental results demonstrate the effectiveness of our proposed framework over existing methods in rendering high-quality and temporally-coherent videos.

AK

375,160 görüntüleme • 3 yıl önce

GPT-5.5 by Reasoning Effort: I've asked it in Codex to create a physics-based visualisation of RL cycles for different sized models (70b, 1t, 10t), to demonstrate how the amount of RL you can do differs by model size. My assessment of each: - Low: weird slop - Medium: kinda cooked - High: sort of tried but ultimately incoherent - Extra High: elite - really nice idea and well executed Obviously this is just one shot, but worth trying different reasoning levels for the new models, medium seems to be pretty good for GPT-5.5 and it was really bad for many previous GPT models.
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GPT-5.5 by Reasoning Effort: I've asked it in Codex to create a physics-based visualisation of RL cycles for different sized models (70b, 1t, 10t), to demonstrate how the amount of RL you can do differs by model size. My assessment of each: - Low: weird slop - Medium: kinda cooked - High: sort of tried but ultimately incoherent - Extra High: elite - really nice idea and well executed Obviously this is just one shot, but worth trying different reasoning levels for the new models, medium seems to be pretty good for GPT-5.5 and it was really bad for many previous GPT models.

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Frontier world models now run on edge GPUs. ⚡ Now openly available, NVIDIA Cosmos 3 Edge brings advanced world-model capabilities to local devices. The 4-billion-parameter omnimodel can understand and generate text, image, video, ambient sound and action for physical AI across robotics, autonomous vehicles and smart infrastructure. 🔗 #SIGGRAPH2026
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Frontier world models now run on edge GPUs. ⚡ Now openly available, NVIDIA Cosmos 3 Edge brings advanced world-model capabilities to local devices. The 4-billion-parameter omnimodel can understand and generate text, image, video, ambient sound and action for physical AI across robotics, autonomous vehicles and smart infrastructure. 🔗 #SIGGRAPH2026

NVIDIA

33,144 görüntüleme • 1 ay önce

Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license
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Gemma 4 is here! Our most intelligent open models to date, are built on the same world-class research and tech as Gemini 3, and are sized to run and fine-tune efficiently on local hardware. Check out what Google Gemma 4 brings to devs: 💎 Advanced Reasoning: Deep logic tasks, complex multi-step planning, and beyond 💎 Longer context: Seamlessly analyze entire codebases with context windows of 128K tokens for our edge models and 256K tokens for our largest models 💎 Vision and audio: Rich, multimodal interactions out of the box 💎 140+ languages: Trained on 140+ languages 💎 Apache 2.0 license: industry-standard open-source license

Google for Developers

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We just discovered the 🔥 COOLEST 🔥 trick in Flow that we have to share: Instead of wordsmithing the perfect prompt, you can just... draw it. Take the image of your scene, doodle what you'd like on it (through any editing app), and then briefly describe what needs to happen (e.g. "changes happen instantly"). Using Frames to Video, Flow will understand the drawings and incorporate them into the final video. Try it and show us what you find!
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We just discovered the 🔥 COOLEST 🔥 trick in Flow that we have to share: Instead of wordsmithing the perfect prompt, you can just... draw it. Take the image of your scene, doodle what you'd like on it (through any editing app), and then briefly describe what needs to happen (e.g. "changes happen instantly"). Using Frames to Video, Flow will understand the drawings and incorporate them into the final video. Try it and show us what you find!

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411,662 görüntüleme • 1 yıl önce

it's over.. this AI agent can build AI apps now I just used Emergent AI to build an AI studio w/o censorship, it can generate and edit images using text and.. you can add any open source models to the studio more examples:
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it's over.. this AI agent can build AI apps now I just used Emergent AI to build an AI studio w/o censorship, it can generate and edit images using text and.. you can add any open source models to the studio more examples:

el.cine

280,948 görüntüleme • 1 yıl önce

1/ Happy to share UniDisc - Unified Multimodal Discrete Diffusion – We train a 1.5 billion parameter transformer model from scratch on 250 million image/caption pairs using a **discrete diffusion objective**. Our model has all the benefits of diffusion models but now in multimodal space! - flexible compute-quality tradeoff, zero-shot inpainting and editing, better control via classifier-free guidance and lower latency! We open source everything - our code, weights and the training dataset.
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1/ Happy to share UniDisc - Unified Multimodal Discrete Diffusion – We train a 1.5 billion parameter transformer model from scratch on 250 million image/caption pairs using a **discrete diffusion objective**. Our model has all the benefits of diffusion models but now in multimodal space! - flexible compute-quality tradeoff, zero-shot inpainting and editing, better control via classifier-free guidance and lower latency! We open source everything - our code, weights and the training dataset.

Mihir Prabhudesai

104,934 görüntüleme • 1 yıl önce

AI compositing is alr taking over now you can edit video like editing image using Seedance 2.0 on Higgsfield, it auto select any object, edit separately and.. even blend in the scene perfectly its just faster, cheaper and more accurate here's how to do + prompts:
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AI compositing is alr taking over now you can edit video like editing image using Seedance 2.0 on Higgsfield, it auto select any object, edit separately and.. even blend in the scene perfectly its just faster, cheaper and more accurate here's how to do + prompts:

el.cine

83,524 görüntüleme • 4 ay önce

added video support to the cmyk halftone emulator! — it's free & open-source, runs in your browser — tons of controls — can record the result into webm or just save the image
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added video support to the cmyk halftone emulator! — it's free & open-source, runs in your browser — tons of controls — can record the result into webm or just save the image

daniel petho

59,752 görüntüleme • 8 ay önce

Someone got tired of paying for Higgsfield and built the free version instead. Its called Open Generative AI → Packs 200+ models into one self-hosted interface. →Text to image, text to video, image to image → Cinema mode with actual camera controls → Your files never leave your machine Getting 200+ models talking to each other under one roof isn't a two-minute setup, but once it's running there's no subscription left to cancel. 100% Open-source.
0:14

Someone got tired of paying for Higgsfield and built the free version instead. Its called Open Generative AI → Packs 200+ models into one self-hosted interface. →Text to image, text to video, image to image → Cinema mode with actual camera controls → Your files never leave your machine Getting 200+ models talking to each other under one roof isn't a two-minute setup, but once it's running there's no subscription left to cancel. 100% Open-source.

Oliver Prompts

13,011 görüntüleme • 26 gün önce

Yup, a football video. The World Cup made us do it Luma rebuilt image generation from scratch — reasoning first, pixels second. And it beats Google's Nano Banana 2 and GPT Image 1.5 on reasoning benchmarks All 3 new models are now live on AI/ML API luma/uni-1 plans before it draws. The model generates autoregressively: it works out layout, composition and text placement first, then renders the pixels. $0.052/image luma/uni-1-max — same prompts, same params, max fidelity. 2K output + editing with up to 9 reference images. Built for hero shots and ad creative. $0.13/image luma/ray-3-2 — up to 16 keyframes per clip, 20s, 1080p, native HDR + 16-bit EXR export. The video in this post came straight out of it model ids "luma/uni-1" "luma/uni-1-max" "luma/ray-3-2" Luma cooked. We serve
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Yup, a football video. The World Cup made us do it Luma rebuilt image generation from scratch — reasoning first, pixels second. And it beats Google's Nano Banana 2 and GPT Image 1.5 on reasoning benchmarks All 3 new models are now live on AI/ML API luma/uni-1 plans before it draws. The model generates autoregressively: it works out layout, composition and text placement first, then renders the pixels. $0.052/image luma/uni-1-max — same prompts, same params, max fidelity. 2K output + editing with up to 9 reference images. Built for hero shots and ad creative. $0.13/image luma/ray-3-2 — up to 16 keyframes per clip, 20s, 1080p, native HDR + 16-bit EXR export. The video in this post came straight out of it model ids "luma/uni-1" "luma/uni-1-max" "luma/ray-3-2" Luma cooked. We serve

AI/ML API

19,375 görüntüleme • 1 ay önce

From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽
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From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽

Teodora P L

28,523 görüntüleme • 1 yıl önce