4 citations · 6 across the 6 of their papers we have counts for
7 papers · 1 filter
Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection
Shichao Li, Peiliang Li, Qing Lian +2
Perceiving pedestrians in highly crowded urban environments is a difficult long-tail problem for learning-based autonomous perception. Speeding up 3D ground truth generation for su…
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving
JunDa Cheng, Wei Yin, Kaixuan Wang +3
Multi-view depth estimation has achieved impressive performance over various benchmarks. However, almost all current multi-view systems rely on given ideal camera poses, which are…
GIM: Learning Generalizable Image Matcher From Internet Videos
Xuelun Shen, Zhipeng Cai, Wei Yin +5
Image matching is a fundamental computer vision problem. While learning-based methods achieve state-of-the-art performance on existing benchmarks, they generalize poorly to in-the-…
Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image
Wei Yin, Chi Zhang, Hao Chen +5
Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-posedness of the single-image reconstruction problem, most well-established methods are…
The Second Monocular Depth Estimation Challenge
Jaime Spencer, C. Stella Qian, Michaela Trescakova +40
This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, includin…
Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes
Rui Li, Dong Gong, Wei Yin +6
Multi-frame depth estimation generally achieves high accuracy relying on the multi-view geometric consistency. When applied in dynamic scenes, e.g., autonomous driving, this consis…