Paper Info
Title
MMDetection: Open MMLab Detection Toolbox and Benchmark.
Abstract
We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The toolbox started from a codebase of MMDet team who won the detection track of COCO Challenge 2018. It gradually evolves into a unified platform that covers many popular detection methods and contemporary modules. It not only includes training and inference codes, but also provides weights for more than 200 network models. We believe this toolbox is by far the most complete detection toolbox. In this paper, we introduce the various features of this toolbox. In addition, we also conduct a benchmarking study on different methods, components, and their hyper-parameters. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new detectors. Code and models are available at https://github.com/open-mmlab/mmdetection. The project is under active development and we will keep this document updated.
Year
Venue
DocType
2019
CoRR
Journal
Volume
Citations 
PageRank 
abs/1906.07155
0
0.34
References 
Authors
0
25
Name
Order
Citations
PageRank
Kai Chen100.68
Jiaqi Wang2774.20
Jiangmiao Pang31106.64
Yuhang Cao400.34
Yu Xiong5482.72
Xiaoxiao Li62539.86
Shuyang Sun7492.06
Wansen Feng8471.35
Ziwei Liu9136163.23
Jiarui Xu1092.48
Zheng Zhang118731.73
Dazhi Cheng1210.68
Chenchen Zhu13796.07
Tianheng Cheng14121.18
Qijie Zhao15113.30
Buyu Li16302.80
Xin Lu173911.66
Rui Zhu18154.81
Yue Wu1933131.69
Jifeng Dai20119042.41
Jingdong Wang214198156.76
Jianping Shi2292043.57
Wanli Ouyang232371105.17
Chen Change Loy244484178.56
Dahua Lin25111772.62