17 citations · 23 across the 16 of their papers we have counts for
6 papers · 1 filter
UIR-LoRA: Achieving Universal Image Restoration through Multiple Low-Rank Adaptation
Cheng Zhang, Dong Gong, Jiumei He +3
Existing unified methods typically treat multi-degradation image restoration as a multi-task learning problem. Despite performing effectively compared to single degradation restora…
Multi-Granularity Language-Guided Training for Multi-Object Tracking
Yuhao Li, Jiale Cao, Muzammal Naseer +4
Most existing multi-object tracking methods typically learn visual tracking features via maximizing dis-similarities of different instances and minimizing similarities of the same…
The Third Monocular Depth Estimation Challenge
Jaime Spencer, Fabio Tosi, Matteo Poggi +38
This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-…
GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
Jiang Wu, Rui Li, Haofei Xu +4
Matching cost aggregation plays a fundamental role in learning-based multi-view stereo networks. However, directly aggregating adjacent costs can lead to suboptimal results due to…
Generating Content for HDR Deghosting from Frequency View
Tao Hu, Qingsen Yan, Yuankai Qi +1
Recovering ghost-free High Dynamic Range (HDR) images from multiple Low Dynamic Range (LDR) images becomes challenging when the LDR images exhibit saturation and significant motion…
Boosting Multi-view Stereo with Late Cost Aggregation
Jiang Wu, Rui Li, Yu Zhu +3
Pairwise matching cost aggregation is a crucial step for modern learning-based Multi-view Stereo (MVS). Prior works adopt an early aggregation scheme, which adds up pairwise costs…