Exploring Long Tailed Visual Recognition
Exploring Long Tailed Visual Recognition reveals several interesting facts.
- Authors: Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan Description: Object ...
- Authors: Boyan Zhou, Quan Cui, Xiu-Shen Wei, Zhao-Min Chen Description: Our work focuses on tackling the challenging but ...
- Authors: Shan Zhang; Yao Ni; Jinhao Du; Yanxia Liu; Piotr Koniusz Description: Deep neural networks excel in
- IJCAI 2021 LTDL workshop Invited Talk 2. Speaker: Boqing Gong.
- Well, was bored Didn't want to play cards, so did a small video explaining a paper on
In-Depth Information on Long Tailed Visual Recognition
Authors: Linchao Zhu, Yi Yang Description: There have been increasing interests in modeling CVPR 2023 paper: FCC: Feature Clusters Compression for Authors: Park, Changhwa; Yim, Junho; Jun, Eunji* Description: Deep neural networks perform well in artificially-balanced datasets ... This is a video of the following paper:
Methods of bridging the performance gap for systems like self-driving cars where failure is not an option.
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