1 citations · 2 across the 7 of their papers we have counts for
9 papers
Self-Improving 4D Perception via Self-Distillation
Nan Huang, Pengcheng Yu, Weijia Zeng +4
Large-scale multi-view reconstruction models have made remarkable progress, but most existing approaches still rely on fully supervised training with ground-truth 3D/4D annotations…
Emergent Outlier View Rejection in Visual Geometry Grounded Transformers
Jisang Han, Sunghwan Hong, Jaewoo Jung +5
Reliable 3D reconstruction from in-the-wild image collections is often hindered by "noisy" images-irrelevant inputs with little or no view overlap with others. While traditional St…
E-RayZer: Self-supervised 3D Reconstruction as Spatial Visual Pre-training
Qitao Zhao, Hao Tan, Qianqian Wang +5
Self-supervised pre-training has driven rapid progress in foundation models for language, 2D images, and video, yet remains largely unexplored for learning 3D-aware representations…
St4RTrack: Simultaneous 4D Reconstruction and Tracking in the World
Haiwen Feng, Junyi Zhang, Qianqian Wang +5
Dynamic 3D reconstruction and point tracking in videos are typically treated as separate tasks, despite their deep connection. We propose St4RTrack, a feed-forward framework that s…
Segment Any Motion in Videos
Nan Huang, Wenzhao Zheng, Chenfeng Xu +4
Moving object segmentation is a crucial task for achieving a high-level understanding of visual scenes and has numerous downstream applications. Humans can effortlessly segment mov…
Continuous 3D Perception Model with Persistent State
Qianqian Wang, Yifei Zhang, Aleksander Holynski +2
We present a unified framework capable of solving a broad range of 3D tasks. Our approach features a stateful recurrent model that continuously updates its state representation wit…
MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos
Zhengqi Li, Richard Tucker, Forrester Cole +6
We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes. Most conventional stru…
Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction
Justin Kerr, Chung Min Kim, Mingxuan Wu +4
Humans can learn to manipulate new objects by simply watching others; providing robots with the ability to learn from such demonstrations would enable a natural interface specifyin…
Shape of Motion: 4D Reconstruction from a Single Video
Qianqian Wang, Vickie Ye, Hang Gao +4
Monocular dynamic reconstruction is a challenging and long-standing vision problem due to the highly ill-posed nature of the task. Existing approaches depend on templates, are effe…