alternative/better paper title: "Use The Force!" (thanks Dan Goldman)

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)

In this blog post we will summarize some of our findings with training autoencoders for diffusion! We also share some null results we had with a slightly unconventional approach we tried. 1/2

I'm in #CVPR2025! Fri, 13 Jun, 4-6 PM CAT, poster session 2 At ExHall D Poster #230 come and have a chat about our work! wang-sj16.github.io/motif/

Had a great time at this CVPR community-building workshop---lots of fun discussions and some really important insights for early-career researchers. I also gave a talk on "Research as an Infinite Game." Here are the slides: canva.com/design/DAGp0iR…

(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.

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,

#ICCV2025 🤩3D world generation is cool, but it is cooler to play with the worlds using 3D actions 👆💨, and see what happens! — Introducing *WonderPlay*: Now you can create dynamic 3D scenes that respond to your 3D actions from a single image! Web: kyleleey.github.io/WonderPlay/ 🧵1/7

🤩 WorldScore is accepted to #ICCV2025. Benchmark your 3D/4D/video world models with WorldScore!

Deep learning training is a mathematical dumpster fire. But it turns out that if you *fix* the math, everything kinda just works…fp8 training, hyperparameter transfer, training stability, and more. [1/n]

Compression is the heart of intelligence From Occam to Kolmogorov—shorter programs=smarter representations Meet KARL: Kolmogorov-Approximating Representation Learning. Given an image, token budget T & target quality 𝜖 —KARL finds the smallest t≤T to reconstruct it within 𝜖🧵

What exactly is a "world model"? And what limits existing video generation models from being true world models? In my new blog post, I argue that a true video world model must be causal, interactive, persistent, real-time, and physical accurate. xunhuang.me/blogs/world_mo…