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cs.CV2026

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

Tianshuo Xu, Yichen Xie, Depu Meng +5

Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption. This is not simply a capacity p…

cs.CV2026

LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation

Bo Jiang, Depu Meng, Yihan Hu +3

Modern video generators produce visually compelling clips but still struggle with physical and motion consistency, limiting their use as reliable world simulators. Existing remedie…

cs.CV2026

EndoVGGT: GNN-Enhanced Depth Estimation for Surgical 3D Reconstruction

Falong Fan, Yi Xie, Arnis Lektauers +2

Accurate 3D reconstruction of deformable soft tissues is essential for surgical robotic perception. However, low-texture surfaces, specular highlights, and instrument occlusions of…

cs.CV2026

UniQueR: Unified Query-based Feedforward 3D Reconstruction

Chensheng Peng, Quentin Herau, Jiezhi Yang +6

We present UniQueR, a unified query-based feedforward framework for efficient and accurate 3D reconstruction from unposed images. Existing feedforward models such as DUSt3R, VGGT,…

cs.CV2026

RAYNOVA: Scale-Temporal Autoregressive World Modeling in Ray Space

Yichen Xie, Chensheng Peng, Mazen Abdelfattah +6

World foundation models aim to simulate the evolution of the real world with physically plausible behavior. Unlike prior methods that handle spatial and temporal correlations separ…

cs.CV2025

DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving Scenes

Chensheng Peng, Chengwei Zhang, Yixiao Wang +6

We present DeSiRe-GS, a self-supervised gaussian splatting representation, enabling effective static-dynamic decomposition and high-fidelity surface reconstruction in complex drivi…