L
Li Wang
Researcher at Fudan University
Publications - 16
Citations - 1733
Li Wang is an academic researcher from Fudan University. The author has contributed to research in topics: Object detection & Feature (computer vision). The author has an hindex of 8, co-authored 15 publications receiving 1177 citations. Previous affiliations of Li Wang include Chinese Academy of Sciences.
Papers
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Journal ArticleDOI
Arbitrary-Oriented Scene Text Detection via Rotation Proposals
TL;DR: The Rotation Region Proposal Networks are designed to generate inclined proposals with text orientation angle information that are adapted for bounding box regression to make the proposals more accurately fit into the text region in terms of the orientation.
Journal ArticleDOI
Arbitrary-Oriented Scene Text Detection via Rotation Proposals
TL;DR: RRPN as mentioned in this paper proposes a rotation region proposal network to generate inclined text proposals with text orientation angle information, which is then adapted for bounding box regression to make the proposals more accurately fit into the text region in terms of the orientation.
Proceedings ArticleDOI
Evolving boxes for fast vehicle detection
TL;DR: It is shown intriguingly that by applying different feature fusion techniques, the initial boxes can be refined for both localization and recognition.
Proceedings ArticleDOI
UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring
Siwei Lyu,Ming-Ching Chang,Dawei Du,Longyin Wen,Honggang Qi,Yuezun Li,Yi Wei,Lipeng Ke,Tao Hu,Marco Del Coco,Pierluigi Carcagnì,Dmitriy Anisimov,Erik Bochinski,Fabio Galasso,Filiz Bunyak,Guang Han,Hao Ye,Hong Wang,Kannappan Palaniappan,Koray Ozcan,Li Wang,Liang Wang,Martin Lauer,Nattachai Watcharapinchai,Nenghui Song,Noor M. Al-Shakarji,Shuo Wang,Sikandar Amin,Sitapa Rujikietgumjorn,Tatiana Khanova,Thomas Sikora,Tino Kutschbach,Volker Eiselein,Wei Tian,Xiangyang Xue,Xiaoyi Yu,Yao Lu,Yingbin Zheng,Yongzhen Huang,Yuqi Zhang +39 more
TL;DR: The AVSS2017 Challenge on Advanced Traffic Monitoring, in conjunction with the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S), to evaluate the state-of-the-art object detection and multi-object tracking algorithms in the relevance of traffic surveillance.
Proceedings ArticleDOI
Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection
TL;DR: A depth-conditioned dynamic message propagation (DDMP) network to effectively integrate the multi-scale depth information with the image context and dynamically predicting hybrid depth-dependent filter weights and affinity matrices for propagating information is proposed.