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Augment and Criticize: Exploring Informative Samples for Semi-Supervised
  Monocular 3D Object Detection

Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection

20 March 2023
Zhenyu Li
Zhipeng Zhang
Heng Fan
Yuan He
Ke Wang
Xianming Liu
Junjun Jiang
ArXivPDFHTML

Papers citing "Augment and Criticize: Exploring Informative Samples for Semi-Supervised Monocular 3D Object Detection"

4 / 4 papers shown
Title
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning
  Framework for Monocular 3D Object Detection
Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection
Lei Yang
Xinyu Zhang
Li-e Wang
Minghan Zhu
Chuan-Fang Zhang
Jun Li
28
30
0
10 Jul 2022
Semi-Supervised Object Detection with Adaptive Class-Rebalancing
  Self-Training
Semi-Supervised Object Detection with Adaptive Class-Rebalancing Self-Training
Fangyuan Zhang
Tianxiang Pan
Bin Wang
26
54
0
11 Jul 2021
Categorical Depth Distribution Network for Monocular 3D Object Detection
Categorical Depth Distribution Network for Monocular 3D Object Detection
Cody Reading
Ali Harakeh
Julia Chae
Steven L. Waslander
3DPC
213
483
0
01 Mar 2021
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
238
3,359
0
09 Mar 2020
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