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20242026
most citedPartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models

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cs.CV2026

PhysiFormer: Learning to Simulate Mechanics in World Space

Yiming Chen, Yushi Lan, Andrea Vedaldi

We present PhysiFormer, a diffusion transformer for physically-plausible 3D object motion. Unlike video world models that operate in view-dependent pixel space, PhysiFormer represe…

cs.CV2026

NOVA3R: Non-pixel-aligned Visual Transformer for Amodal 3D Reconstruction

Weirong Chen, Chuanxia Zheng, Ganlin Zhang +2

We present NOVA3R, an effective approach for non-pixel-aligned 3D reconstruction from a set of unposed images in a feed-forward manner. Unlike pixel-aligned methods that tie geomet…

cs.CV2026

CoWTracker: Tracking by Warping instead of Correlation

Zihang Lai, Eldar Insafutdinov, Edgar Sucar +1

Dense point tracking is a fundamental problem in computer vision, with applications ranging from video analysis to robotic manipulation. State-of-the-art trackers typically rely on…

cs.CV2026

V-DPM: 4D Video Reconstruction with Dynamic Point Maps

Edgar Sucar, Eldar Insafutdinov, Zihang Lai +1

Powerful 3D representations such as DUSt3R invariant point maps, which encode 3D shape and camera parameters, have significantly advanced feed forward 3D reconstruction. While poin…

cs.CV2026

Mesh4D: 4D Mesh Reconstruction and Tracking from Monocular Video

Zeren Jiang, Chuanxia Zheng, Iro Laina +2

We propose Mesh4D, a feed-forward model for monocular 4D mesh reconstruction. Given a monocular video of a dynamic object, our model reconstructs the object's complete 3D shape and…

cs.CV2026

LaVR: Scene Latent Conditioned Generative Video Trajectory Re-Rendering using Large 4D Reconstruction Models

Mingyang Xie, Numair Khan, Tianfu Wang +8

Given a monocular video, the goal of video re-rendering is to generate views of the scene from a novel camera trajectory. Existing methods face two distinct challenges. Geometrical…