1 citations · 1 across the 5 of their papers we have counts for
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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…
OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models
Yiwei Zhang, Xuesong Chen, Jin Gao +5
Vision-Language Models(VLMs) excel at autoregressive text generation, yet end-to-end autonomous driving requires multi-task learning with structured outputs and heterogeneous decod…
MMPhysVideo: Physically Plausible Video Generation Through Joint RGB-Perception Modeling
Shubo Lin, Xuanyang Zhang, Wei Cheng +3
Despite advancements in generating visually stunning content, video diffusion models (VDMs) often yield physically inconsistent results due to pixel-only reconstruction. To address…
Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
Yanqin Jiang, Chaohui Yu, Chenjie Cao +3
Recent advances in 4D generation mainly focus on generating 4D content by distilling pre-trained text or single-view image-conditioned models. It is inconvenient for them to take a…
Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video
Yanqin Jiang, Li Zhang, Jin Gao +2
In this paper, we present Consistent4D, a novel approach for generating 4D dynamic objects from uncalibrated monocular videos. Uniquely, we cast the 360-degree dynamic object recon…