7 papers
Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction
Tao Xie, Peishan Yang, Yudong Jin +8
This paper addresses the task of large-scale 3D scene reconstruction from long video sequences. Recent feed-forward reconstruction models have shown promising results by directly r…
FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views
Shangzhan Zhang, Jianyuan Wang, Yinghao Xu +5
We present FLARE, a feed-forward model designed to infer high-quality camera poses and 3D geometry from uncalibrated sparse-view images (i.e., as few as 2-8 inputs), which is a cha…
BoxDreamer: Dreaming Box Corners for Generalizable Object Pose Estimation
Yuanhong Yu, Xingyi He, Chen Zhao +7
This paper presents a generalizable RGB-based approach for object pose estimation, specifically designed to address challenges in sparse-view settings. While existing methods can e…
PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes
Xiao Fu, Shangzhan Zhang, Tianrun Chen +4
Training perception systems for self-driving cars requires substantial 2D annotations that are labor-intensive to manual label. While existing datasets provide rich annotations on…
MASH: Masked Anchored SpHerical Distances for 3D Shape Representation and Generation
Changhao Li, Yu Xin, Xiaowei Zhou +4
We introduce Masked Anchored SpHerical Distances (MASH), a novel multi-view and parametrized representation of 3D shapes. Inspired by multi-view geometry and motivated by the impor…
MaPa: Text-driven Photorealistic Material Painting for 3D Shapes
Shangzan Zhang, Sida Peng, Tao Xu +7
This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural mat…