5 papers
Rethinking Asymmetry in Self-Supervised 3D Geometry Learning
Gyeongjin Kang, Freeman Cheng, Botao Ye +3
Self-supervised learning relies on asymmetry between what a model observes and what it must explain. Recent methods learn 3D geometry from unposed images by predicting cameras and…
Reconstructing the Dynamic World: A Representation-Centric View of 4D Scene Reconstruction
Ziren Gong, Guo Chen, Yongjia Li +13
4D scene reconstruction aims to recover the evolving geometry, appearance, and motion of dynamic environments from visual observations. Despite substantial progress in neural scene…
OmniPoint: Universal Monocular Metric Pointcloud from Any Camera
Botao Ye, Marc Pollefeys, Ming-Hsuan Yang +1
Recovering metric 3D geometry from monocular images is a fundamental computer vision task, yet current methods remain heavily fragmented by fixed camera model assumptions and infle…
ReCoSplat: Online Feed-Forward Gaussian Splatting via Render-and-Compare
Freeman Cheng, Botao Ye, Xueting Li +3
Online novel view synthesis requires a model to reconstruct a scene causally from a stream of observations while keeping it renderable at every moment. We present ReCoSplat, an onl…
SAW-Bench: Learning Situated Awareness in the Real World
Chuhan Li, Rilyn Han, Joy Hsu +5
A core aspect of human perception is situated awareness, the ability to relate ourselves to the surrounding physical environment and reason over possible actions in context. Howeve…