Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised
Object Detection

Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection

17 July 2022

Lei Zhang

Papers citing "Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection"

6 / 6 papers shown

Title
Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Images Ruixiang Zhang Chang Xu Fang Xu Wen Yang Guangjun He Huai Yu Gui-Song Xia 49 2 0 23 Oct 2023
Training-based Model Refinement and Representation Disagreement for Semi-Supervised Object Detection S. M. Marvasti-Zadeh Nilanjan Ray Nadir Erbilgin 27 1 0 25 Jul 2023
Revisiting Class Imbalance for End-to-end Semi-Supervised Object Detection P. Kar Vishal M. Chudasama N. Onoe Pankaj Wasnik 28 8 0 04 Jun 2023
MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection Liang Liu Boshen Zhang Jiangning Zhang Wuhao Zhang Zhenye Gan Guanzhong Tian Wenjie Zhu Yabiao Wang Chengjie Wang 16 27 0 16 Mar 2023
Revisiting the Sibling Head in Object Detector Guanglu Song Yu Liu Xiaogang Wang ObjD 181 348 0 17 Mar 2020
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 261 1,275 0 06 Mar 2017