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cs.CV2026

Pantheon360: Taming Digital Twin Generation via 3D-Aware 360° Video Diffusion

Ting-Hsuan Chen, Ying-Huan Chen, Tao Tu +10

Generating complete digital twins from videos requires precise camera control, global scene coverage, and strict spatial-temporal consistency constraints that remain challenging fo…

cs.CV2026

VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation

Hongyang Du, Junjie Ye, Xiaoyan Cong +7

While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deforma…

cs.CV2025

Neural Eulerian Scene Flow Fields

Kyle Vedder, Neehar Peri, Ishan Khatri +7

We reframe scene flow as the task of estimating a continuous space-time ODE that describes motion for an entire observation sequence, represented with a neural prior. Our method, E…

cs.CV2025

Discriminately Treating Motion Components Evolves Joint Depth and Ego-Motion Learning

Mengtan Zhang, Zizhan Guo, Hongbo Zhao +6

Unsupervised learning of depth and ego-motion, two fundamental 3D perception tasks, has made significant strides in recent years. However, most methods treat ego-motion as an auxil…

cs.CV2025

SaLon3R: Structure-aware Long-term Generalizable 3D Reconstruction from Unposed Images

Jiaxin Guo, Tongfan Guan, Wenzhen Dong +5

Recent advances in 3D Gaussian Splatting (3DGS) have enabled generalizable, on-the-fly reconstruction of sequential input views. However, existing methods often predict per-pixel G…

cs.CV2025

SIRE: SE(3) Intrinsic Rigidity Embeddings

Cameron Smith, Basile Van Hoorick, Vitor Guizilini +1

Motion serves as a powerful cue for scene perception and understanding by separating independently moving surfaces and organizing the physical world into distinct entities. We intr…