9 papers · 1 filter
OmniX: Any-view and Any-time 4D Reconstruction via Feed-forward Trajectory Fields
Yanqin Jiang, Tengfei Wang, Zhengwei Wang +6
Previous feed-forward 4D reconstruction methods either predict per-frame static point clouds, ignoring foreground motion, or estimate point cloud trajectories while being limited t…
HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds
Team HY-World, Chenjie Cao, Xuhui Zuo +42
We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prom…
WorldStereo: Bridging Camera-Guided Video Generation and Scene Reconstruction via 3D Geometric Memories
Yisu Zhang, Chenjie Cao, Tengfei Wang +4
Recent advances in foundational Video Diffusion Models (VDMs) have yielded significant progress. Yet, despite the remarkable visual quality of generated videos, reconstructing cons…
RealisMotion: Decomposed Human Motion Control and Video Generation in the World Space
Jingyun Liang, Jingkai Zhou, Shikai Li +5
Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control ov…
EarthCrafter: Scalable 3D Earth Generation via Dual-Sparse Latent Diffusion
Shang Liu, Chenjie Cao, Chaohui Yu +3
Despite the remarkable developments achieved by recent 3D generation works, scaling these methods to geographic extents, such as modeling thousands of square kilometers of Earth's…
LiON-LoRA: Rethinking LoRA Fusion to Unify Controllable Spatial and Temporal Generation for Video Diffusion
Yisu Zhang, Chenjie Cao, Chaohui Yu +1
Video Diffusion Models (VDMs) have demonstrated remarkable capabilities in synthesizing realistic videos by learning from large-scale data. Although vanilla Low-Rank Adaptation (Lo…