6 papers · 1 filter
UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching
Qilin Huang, Quynh Anh Huynh, Long Le +5
Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamentally fails to capture the r…
PhyWorld: Physics-Faithful World Model for Video Generation
Pu Zhao, Juyi Lin, Timothy Rupprecht +10
World simulators can provide safe and scalable environments for training Physical AI systems before real-world deployment. Large video generation models are emerging as a promising…
OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation
Yuheng Liu, Xin Lin, Xinke Li +9
Modeling scenes using video generation models has garnered growing research interest in recent years. However, most existing approaches rely on perspective video models that synthe…
DIMO: Diverse 3D Motion Generation for Arbitrary Objects
Linzhan Mou, Jiahui Lei, Chen Wang +2
We present DIMO, a generative approach capable of generating diverse 3D motions for arbitrary objects from a single image. The core idea of our work is to leverage the rich priors…
StereoDiff: Stereo-Diffusion Synergy for Video Depth Estimation
Haodong Li, Chen Wang, Jiahui Lei +2
Recent video depth estimation methods achieve great performance by following the paradigm of image depth estimation, i.e., typically fine-tuning pre-trained video diffusion models…
Zero-1-to-G: Taming Pretrained 2D Diffusion Model for Direct 3D Generation
Xuyi Meng, Chen Wang, Jiahui Lei +3
Recent advances in 2D image generation have achieved remarkable quality,largely driven by the capacity of diffusion models and the availability of large-scale datasets. However, di…