674 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Illinois ChicagoUS13 papers
- Singapore Management UniversitySG11 papers
- Carnegie Mellon UniversityUS8 papers
- Georgia Institute of TechnologyUS7 papers
- Princeton UniversityUS7 papers
- Nanyang Technological UniversitySG6 papers
- University of Illinois Urbana-ChampaignUS6 papers
- Agency for Science, Technology and ResearchSG5 papers
- Chinese University of Hong KongHK5 papers
- University of Maryland, College ParkUS5 papers
- University of WashingtonUS5 papers
- Beihang UniversityCN4 papers
6 papers · 2 filters
Learning from Noisy Anchors for One-stage Object Detection
Hengduo Li, Zuxuan Wu, Chen Zhu +3
State-of-the-art object detectors rely on regressing and classifying an extensive list of possible anchors, which are divided into positive and negative samples based on their inte…
Classification Calibration for Long-tail Instance Segmentation
Tao Wang, Yu Li, Bingyi Kang +5
Remarkable progress has been made in object instance detection and segmentation in recent years. However, existing state-of-the-art methods are mostly evaluated with fairly balance…
WSLLN: Weakly Supervised Natural Language Localization Networks
Mingfei Gao, Larry S. Davis, Richard Socher +1
We propose weakly supervised language localization networks (WSLLN) to detect events in long, untrimmed videos given language queries. To learn the correspondence between visual se…
Recent Advances in Deep Learning for Object Detection
Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi
Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades. Visual object detection aims to find objects of cer…
Distilled Siamese Networks for Visual Tracking
Jianbing Shen, Yuanpei Liu, Xingping Dong +3
In recent years, Siamese network based trackers have significantly advanced the state-of-the-art in real-time tracking. Despite their success, Siamese trackers tend to suffer from…
Deep Learning for Image Super-resolution: A Survey
Zhihao Wang, Jian Chen, Steven C. H. Hoi
Image Super-Resolution (SR) is an important class of image processing techniques to enhance the resolution of images and videos in computer vision. Recent years have witnessed rema…