6 papers
Vision Pretraining for Dense Spatial Perception
Zelin Fu, Bin Tan, Changjiang Sun +6
Dense spatial perception is essential for physical intelligence, where visual systems are expected to recover structured, metric, and actionable representations from pixel observat…
Tac-DINO: Learning Vision-Tactile Features with Patch Alignment
Hong Li, Yankang Dong, Yue Xu +8
Touch is the primary medium through which humans interact with the environment. Currently, tactile learning mainly focuses on image-level pretraining or alignment. However, tactile…
Seeing through Satellite Images at Street Views
Ming Qian, Bin Tan, Qiuyu Wang +5
This paper studies the task of SatStreet-view synthesis, which aims to render photorealistic street-view panorama images and videos given any satellite image and specified camera p…
Interacted Planes Reveal 3D Line Mapping
Zeran Ke, Bin Tan, Gui-Song Xia +2
3D line mapping from multi-view RGB images provides a compact and structured visual representation of scenes. We study the problem from a physical and topological perspective: a 3D…
PLANA3R: Zero-shot Metric Planar 3D Reconstruction via Feed-Forward Planar Splatting
Changkun Liu, Bin Tan, Zeran Ke +6
This paper addresses metric 3D reconstruction of indoor scenes by exploiting their inherent geometric regularities with compact representations. Using planar 3D primitives - a well…
ScaleLSD: Scalable Deep Line Segment Detection Streamlined
Zeran Ke, Bin Tan, Xianwei Zheng +3
This paper studies the problem of Line Segment Detection (LSD) for the characterization of line geometry in images, with the aim of learning a domain-agnostic robust LSD model that…