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Paper rejected from #CVPR2025, paper ready for #ICCV2025 💪

Paper rejected from #CVPR2025, paper ready for #ICCV2025 💪

787,989 просмотров • 1 год назад

The code of GSPN #CVPR2025 is released! We proposed a new sqrt(N) complexity attention mechanism, which enables efficient high resolution image generation. We can generate 8k images with 42x speed up compared to self-attention in StableDiffusionXL! Code: Paper:

The code of GSPN #CVPR2025 is released! We proposed a new sqrt(N) complexity attention mechanism, which enables efficient high resolution image generation. We can generate 8k images with 42x speed up compared to self-attention in StableDiffusionXL! Code: Paper:

354,791 просмотров • 1 год назад

Spatial reasoning is a major challenge for the foundation models today, even in simple tasks like arranging objects in 3D space. #CVPR2025 Introducing LayoutVLM, a differentiable optimization framework that uses VLM to spatially reason about diverse scene layouts from unlabeled assets and open-ended language instructions 1/n

Spatial reasoning is a major challenge for the foundation models today, even in simple tasks like arranging objects in 3D space. #CVPR2025 Introducing LayoutVLM, a differentiable optimization framework that uses VLM to spatially reason about diverse scene layouts from unlabeled assets and open-ended language instructions 1/n

92,514 просмотров • 1 год назад

⚡️ Excited to announce Fast3R: 3D reconstruction of 1000+ images in a single forward pass! Fast3R achieves 251 FPS at its peak. 🔥 Try the demo with your images or video! 🔗 Website: 🎮 Demo: #CVPR2025 #3D AI at Meta

⚡️ Excited to announce Fast3R: 3D reconstruction of 1000+ images in a single forward pass! Fast3R achieves 251 FPS at its peak. 🔥 Try the demo with your images or video! 🔗 Website: 🎮 Demo: #CVPR2025 #3D AI at Meta

Jianing “Jed” Yang

71,665 просмотров • 1 год назад

🚀Excited to introduce GEN3C #CVPR2025, a generative video model with an explicit 3D cache for precise camera control. 🎥It applies to multiple use cases, including single-view and sparse-view NVS🖼️ and challenging settings like monocular dynamic NVS and driving simulation🚗. Project page:

🚀Excited to introduce GEN3C #CVPR2025, a generative video model with an explicit 3D cache for precise camera control. 🎥It applies to multiple use cases, including single-view and sparse-view NVS🖼️ and challenging settings like monocular dynamic NVS and driving simulation🚗. Project page:

59,920 просмотров • 1 год назад

🚀 Excited to introduce SimWorld: an embodied simulator for infinite photorealistic world generation 🏙️ populated with diverse agents 🤖 If you are at #CVPR2025, come check out the live demo 👇 Jun 14, 12:00-1:00 pm at JHU booth, ExHall B Jun 15, 10:30 am-12:30 pm, #7, ExHall B

🚀 Excited to introduce SimWorld: an embodied simulator for infinite photorealistic world generation 🏙️ populated with diverse agents 🤖 If you are at #CVPR2025, come check out the live demo 👇 Jun 14, 12:00-1:00 pm at JHU booth, ExHall B Jun 15, 10:30 am-12:30 pm, #7, ExHall B

29,516 просмотров • 11 месяцев назад

Next in our #CVPR2025 lineup: PromptHMR 👀✨ Drop a video and watch it blossom into crisp 3D people, even when limbs are hidden or several folks share the frame. Humans reconstructed in world coordinates with state-of-the-art accuracy 💯 By Yufu Wang, Yu Sun, Priyanka Patel, Kostas Daniilidis, Michael J. Black and Muhammed Kocabas. Why it matters • One-click lifelike 3D bodies • Keeps tracking when limbs slip behind objects • Understands interactions in crowded scenes • Anchors every person precisely in real-world space 🎯 Artists, animators, game devs and researchers can plug PromptHMR into their pipeline and generate digital humans in minutes. 🎥 Catch our Difflocks video for hair magic, and visit booth 1333 at #CVPR2026 to see PromptHMR live and chat with the team. 📄 Paper link in the thread/comment. #3D #DigitalHuman #ComputerVision #AI #MachineLearning #SMPL #MotionCapture

Next in our #CVPR2025 lineup: PromptHMR 👀✨ Drop a video and watch it blossom into crisp 3D people, even when limbs are hidden or several folks share the frame. Humans reconstructed in world coordinates with state-of-the-art accuracy 💯 By Yufu Wang, Yu Sun, Priyanka Patel, Kostas Daniilidis, Michael J. Black and Muhammed Kocabas. Why it matters • One-click lifelike 3D bodies • Keeps tracking when limbs slip behind objects • Understands interactions in crowded scenes • Anchors every person precisely in real-world space 🎯 Artists, animators, game devs and researchers can plug PromptHMR into their pipeline and generate digital humans in minutes. 🎥 Catch our Difflocks video for hair magic, and visit booth 1333 at #CVPR2026 to see PromptHMR live and chat with the team. 📄 Paper link in the thread/comment. #3D #DigitalHuman #ComputerVision #AI #MachineLearning #SMPL #MotionCapture

23,696 просмотров • 1 год назад

🚦 Excited introducing Urban-Sim — our new simulator presented at #CVPR2025 as a highlight paper! ⚡️ Fast training with IsaacSim backend 🏙️ Diverse 3D assets for rich urban scenes 🤖 Towards generalizable robots in dynamic urban environments. Webpage:

🚦 Excited introducing Urban-Sim — our new simulator presented at #CVPR2025 as a highlight paper! ⚡️ Fast training with IsaacSim backend 🏙️ Diverse 3D assets for rich urban scenes 🤖 Towards generalizable robots in dynamic urban environments. Webpage:

18,208 просмотров • 1 год назад

On deck in our #CVPR2025 series: ChatGarment 👚✨ By Siyuan Bian, Chenghao Xu, Yuliang Xiu, Artur Grigorev, Zhen Liu, Cewu Lu, Michael J. Black and Yao Feng. Feed it an image, video or text, and watch a tailored 3D outfit appear. The video walks through: 1️⃣ Image-based sewing pattern estimation 2️⃣ Text-to-garment generation 3️⃣ Text-based editing Why it matters • Designers preview new looks before cutting fabric • Game and film studios drop physics-ready clothes onto avatars in minutes • Researchers study cloth–body dynamics without manual labeling 🎯 Crafting catwalk looks or decking out game avatars? Just type a prompt and ChatGarment whips up, shrinks, or totally restyles the outfit—no scissors required! 👋 Swing by our #CVPR2026 booth 1333 to meet some of the minds behind ChatGarment, and stay tuned for more CVPR paper videos! 📄 Paper link in the thread/comment. #GarmentTech #3DFashion #DigitalHuman #ComputerVision #AI #MachineLearning

On deck in our #CVPR2025 series: ChatGarment 👚✨ By Siyuan Bian, Chenghao Xu, Yuliang Xiu, Artur Grigorev, Zhen Liu, Cewu Lu, Michael J. Black and Yao Feng. Feed it an image, video or text, and watch a tailored 3D outfit appear. The video walks through: 1️⃣ Image-based sewing pattern estimation 2️⃣ Text-to-garment generation 3️⃣ Text-based editing Why it matters • Designers preview new looks before cutting fabric • Game and film studios drop physics-ready clothes onto avatars in minutes • Researchers study cloth–body dynamics without manual labeling 🎯 Crafting catwalk looks or decking out game avatars? Just type a prompt and ChatGarment whips up, shrinks, or totally restyles the outfit—no scissors required! 👋 Swing by our #CVPR2026 booth 1333 to meet some of the minds behind ChatGarment, and stay tuned for more CVPR paper videos! 📄 Paper link in the thread/comment. #GarmentTech #3DFashion #DigitalHuman #ComputerVision #AI #MachineLearning

17,522 просмотров • 1 год назад

Existing 3D human manipulation datasets are valuable, but are limited in scale and diversity. At #CVPR2025, we will introduce GigaHands👐 which, to our knowledge, is the most extensive 3D bimanual manipulation, interaction, and gesture dataset.🧵👇(1/9)

Existing 3D human manipulation datasets are valuable, but are limited in scale and diversity. At #CVPR2025, we will introduce GigaHands👐 which, to our knowledge, is the most extensive 3D bimanual manipulation, interaction, and gesture dataset.🧵👇(1/9)

Srinath Sridhar

13,443 просмотров • 1 год назад

Check out 🌟Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry & Physics for Mesh-Free Simulation #CVPR2025, from Lingjie Liu’s lab at UPenn. Congrats to Chuhao Chen! Vid2Sim aims to achieve system identification by reconstructing geometry, appearance, and physical properties directly from video. It combines learned data priors with closed-loop optimization: a feed-forward predictor trained on physical prior, followed by fast refinement via Neural Jacobian and mesh-free simulation. The system delivers simulation-ready outputs in minutes, with strong generalization across objects and materials. 🏠Project page: #PhysicalAI #AIGC #CV #CG #simulation #graphics

Check out 🌟Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry & Physics for Mesh-Free Simulation #CVPR2025, from Lingjie Liu’s lab at UPenn. Congrats to Chuhao Chen! Vid2Sim aims to achieve system identification by reconstructing geometry, appearance, and physical properties directly from video. It combines learned data priors with closed-loop optimization: a feed-forward predictor trained on physical prior, followed by fast refinement via Neural Jacobian and mesh-free simulation. The system delivers simulation-ready outputs in minutes, with strong generalization across objects and materials. 🏠Project page: #PhysicalAI #AIGC #CV #CG #simulation #graphics

Zhiyang (Frank) Dou

12,393 просмотров • 11 месяцев назад

Kudos to the research team at our sister company Eyeline. Their latest research paper, 🌊Go-with-the-Flow 🌊, will be presented at #CVPR2025! Based on their research, we believe this could allow artists in the future to leverage these new techniques to direct the motion in generated videos, empowering creative control in a wide range of video applications: cut-and-drag animation, transferring movement between videos, first frame editing, camera control via depth warping, and text-to-video 3D scene creation. Kudos to the amazing team: Ryan Burgert, Yuancheng Xu, Wenqi Xian, Oliver Pilarski, Pascal Clausen, Mingming He, LiMa, Yitong Deng, Lingxiao Li, Mohsen Mousavi, Michael Ryoo, Paul Debevec, Ning Yu, from Eyeline, Scanline VFX - Powered by Netflix, Netflix, Stony Brook University, University of Maryland, and Stanford University. ***This is part of the ongoing research and development at Eyeline and we hope to see adoption in these techniques and workflows soon. Paper: Web: Code: Models: #MachineLearning #video #VideoGeneration #DiffusionModels #VideoDiffusionModels #OpenSource

Kudos to the research team at our sister company Eyeline. Their latest research paper, 🌊Go-with-the-Flow 🌊, will be presented at #CVPR2025! Based on their research, we believe this could allow artists in the future to leverage these new techniques to direct the motion in generated videos, empowering creative control in a wide range of video applications: cut-and-drag animation, transferring movement between videos, first frame editing, camera control via depth warping, and text-to-video 3D scene creation. Kudos to the amazing team: Ryan Burgert, Yuancheng Xu, Wenqi Xian, Oliver Pilarski, Pascal Clausen, Mingming He, LiMa, Yitong Deng, Lingxiao Li, Mohsen Mousavi, Michael Ryoo, Paul Debevec, Ning Yu, from Eyeline, Scanline VFX - Powered by Netflix, Netflix, Stony Brook University, University of Maryland, and Stanford University. ***This is part of the ongoing research and development at Eyeline and we hope to see adoption in these techniques and workflows soon. Paper: Web: Code: Models: #MachineLearning #video #VideoGeneration #DiffusionModels #VideoDiffusionModels #OpenSource

Scanline VFX - Powered by Netflix

13,887 просмотров • 1 год назад