🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🔥 Introducing MVLift: Generate realistic 3D motion without any 3D training data - just using 2D poses from monocular videos! Applicable to human motion, human-object interaction & animal motion. Joint work w/ Jiajun Wu & Karen 💡 How? We reformulate 3D motion estimation as

🤩Forget MoCap -- Let’s generate human interaction motions with *Real-world 3D scenes*!🏃🏞️ Introducing ZeroHSI: Zero-Shot 4D Human-Scene Interaction by Video Generation. No training, No MoCap data! 🧵1/5 Web: awfuact.github.io/zerohsi/

Excited to bring back the 2nd Workshop on Visual Concepts at #CVPR2025 2025, this time with a call for papers! We welcome submissions on the following topics. See our website for more info: sites.google.com/stanford.edu/w… Join us & a fantastic lineup of speakers in Tennessee!

🚀 3 more days for #3DV2025 early registration! Don’t miss out - register now! We’re featuring: ✨ Keynotes: Fei-Fei Li, Jon Barron, Noah Snavely 🗣️ Panels: Embodied AI & Large Models 📜 Accepted Papers: Oral talks & posters 🌟 Nectar Track: Spotlight talks & posters International Conference on 3D Vision

State-of-the-art zero-shot customized image generation by Shengqu Cai, Eric Chan, Yunzhi Zhang, Leo Guibas, Jiajun Wu !

🤖 Ever wondered what robots need to truly help humans around the house? 🏡 Introducing 𝗕𝗘𝗛𝗔𝗩𝗜𝗢𝗥 𝗥𝗼𝗯𝗼𝘁 𝗦𝘂𝗶𝘁𝗲 (𝗕𝗥𝗦)—a comprehensive framework for mastering mobile whole-body manipulation across diverse household tasks! 🧹🫧 From taking out the trash to

#3DV2025 is happening in 10 days in Singapore, but we can't wait to give some spoilers for the award!! 8 papers were selected as award candidates, congrats 🥳. The final awards will be announced during the main conference. 3dvconf.github.io/2025/awards/

Modern generative models of images and videos rely on tokenizers. Can we build a state-of-the-art discrete image tokenizer with a diffusion autoencoder? Yes! I’m excited to share FlowMo, with Kyle Hsu, Justin Johnson, Fei-Fei Li, Jiajun Wu. A thread 🧵:

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

New paper on self-supervised optical flow and occlusion estimation from video foundation models. Stefan Stojanov Jiajun Wu Seungwoo (Simon) Kim Rahul Venkatesh tinyurl.com/dpa3auzd @

🤩 FluidNexus has been selected as CVPR'25 *Oral* paper 🎺! See you at Nashville!

Introducing T* and LV-Haystack -- targeting needle-in-the-haystack for long videos! 🤗 LV-Haystack annotated 400+ hours of videos and 15,000+ samples. 🧩 Lightweight plugin for any proprietary and open-source VLMs: T* boosting LLaVA-OV-72B [56→62%] and GPT-4o [50→53%] within

🔥Spatial intelligence requires world generation, and now we have the first comprehensive evaluation benchmark📏 for it! Introducing WorldScore: Unifying evaluation for 3D, 4D, and video models on world generation! 🧵1/7 Web: haoyi-duan.github.io/WorldScore/ arxiv: arxiv.org/abs/2504.00983

Stanford AI Lab (SAIL) is excited to announce new SAIL Postdoctoral Fellowships! We are looking for outstanding candidates excited to advance the frontiers of AI with our professors and vibrant community. Applications received by the end of April 30 will receive full

We'll be presenting Deep Schema Grounding at ICLR 2026 🇸🇬 on Thursday (session 1 #98). Come chat about abstract visual concepts, structured decomposition, & what makes a maze a maze! & test your models on our challenging Visual Abstractions Benchmark: stanford.edu/~joycj/project…

How to scale visual affordance learning that is fine-grained, task-conditioned, works in-the-wild, in dynamic envs? Introducing Unsupervised Affordance Distillation (UAD): distills affordances from off-the-shelf foundation models, *all without manual labels*. Very excited this

Neuro-symbolic concepts (object, action, relation) represented by a hybrid of neural nets & symbolic programs. Composable, grounded, and typed, agents recombine them to solve tasks like robotic manipulation. J. Tenenbaum Jiayuan Mao Jiajun Wu Massachusetts Institute of Technology (MIT) arxiv.org/abs/2505.06191

💫 Animating 4D objects is complex: traditional methods rely on handcrafted, category-specific rigging representations. 💡 What if we could learn unified, category-agnostic, and scalable 4D motion representations — from raw, unlabeled data? 🚀 Introducing CANOR at #CVPR2025: a

🚀 Excited to announce our CVPR 2025 Workshop: 3D Digital Twin: Progress, Challenges, and Future Directions 🗓 June 12, 2025 · 9:00 AM–5:00 PM 📢 Incredible lineup: Richard Newcombe, Andrea Vedaldi Visual Geometry Group (VGG),Hao (Richard) Zhang,Qianqian Wang,Dr. Xiaoshuai Zhang Hillbot,

(1/n) Time to unify your favorite visual generative models, VLMs, and simulators for controllable visual generation—Introducing a Product of Experts (PoE) framework for inference-time knowledge composition from heterogeneous models.