Generating Positive Bounding Boxes for Balanced Training of Object
Detectors

v1v2v3 (latest)

Generating Positive Bounding Boxes for Balanced Training of Object Detectors

21 September 2019

ArXiv (abs)PDF HTML Github (30★)

Papers citing "Generating Positive Bounding Boxes for Balanced Training of Object Detectors"

9 / 9 papers shown

Title
A Systematic Review on Long-Tailed Learning Chongsheng Zhang G. Almpanidis Gaojuan Fan Binquan Deng Yanbo Zhang Ji Liu Aouaidjia Kamel Paolo Soda Joao Gama 102 8 0 01 Aug 2024
Self-Balanced R-CNN for Instance Segmentation L. Rossi Akbar Karimi Andrea Prati ISeg SSeg 75 9 0 25 Apr 2024
Class Imbalance in Object Detection: An Experimental Diagnosis and Study of Mitigation Strategies Nieves Crasto ObjD 97 6 0 11 Mar 2024
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration Kemal Oksuz Thomas Joy P. Dokania UQCV 82 16 0 03 Jul 2023
Human Body Pose Estimation for Gait Identification: A Comprehensive Survey of Datasets and Models Luke K. Topham Wasiq Khan D. Al-Jumeily A. Hussain CVBM 105 33 0 23 May 2023
Multi-Expert Human Action Recognition with Hierarchical Super-Class Learning Hojat Asgarian Dehkordi Ali Soltani Nezhad Hossein Kashiani S. B. Shokouhi Ahmad Ayatollahi 72 13 0 13 Dec 2021
Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing L. Rossi Akbar Karimi Andrea Prati 25 4 0 03 Apr 2021
Empirical Upper Bound, Error Diagnosis and Invariance Analysis of Modern Object Detectors Ali Borji ObjD 31 3 0 05 Apr 2020
Imbalance Problems in Object Detection: A Review Kemal Oksuz Baris Can Cam Sinan Kalkan Emre Akbas ObjD 139 470 0 31 Aug 2019