Not All Labels Are Equal: Rationalizing The Labeling Costs for Training
Object Detection

Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection

22 June 2021

Anima Anandkumar

Laura Leal-Taixe

Papers citing "Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection"

10 / 10 papers shown

Title
HeAL3D: Heuristical-enhanced Active Learning for 3D Object Detection Esteban Rivera Surya Prabhakaran Markus Lienkamp VLM 141 0 0 01 May 2025
Breaking the SSL-AL Barrier: A Synergistic Semi-Supervised Active Learning Framework for 3D Object Detection Zengran Wang Yanan Zhang Jiaxin Chen Di Huang 29 0 0 26 Jan 2025
Semi-supervised Active Learning for Video Action Detection Aayush Singh A. J. Rana Akash Kumar Shruti Vyas Y. S. Rawat 28 7 0 12 Dec 2023
Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning A. Hekimoglu Michael Schmidt Alvaro Marcos-Ramiro 3DPC 21 10 0 17 Jul 2023
Exploring Active 3D Object Detection from a Generalization Perspective Yadan Luo Zhuoxiao Chen Zijian Wang Xin Yu Zi Huang Mahsa Baktash 3DPC 24 26 0 23 Jan 2023
Active Learning Strategies for Weakly-supervised Object Detection Huy V. Vo Oriane Siméoni Spyros Gidaris Andrei Bursuc Patrick Pérez Jean Ponce 14 19 0 25 Jul 2022
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 221 862 0 15 Oct 2021
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost M. Gao Zizhao Zhang Guo-Ding Yu Sercan Ö. Arik L. Davis Tomas Pfister 158 195 0 16 Oct 2019
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 244 1,275 0 06 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 261 9,134 0 06 Jun 2015