Rethinking Pseudo Labels for Semi-Supervised Object Detection

Rethinking Pseudo Labels for Semi-Supervised Object Detection

1 June 2021

Zuxuan Wu

Abhinav Shrivastava

Papers citing "Rethinking Pseudo Labels for Semi-Supervised Object Detection"

8 / 8 papers shown

Title
Semi-rPPG: Semi-Supervised Remote Physiological Measurement with Curriculum Pseudo-Labeling Bingjie Wu Zitong Yu Yiping Xie Wei Liu Chaoqi Luo Yong Liu Rick Siow Mong Goh 64 0 0 06 Feb 2025
Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection Farzad Nozarian Shashank Agarwal Farzaneh Rezaeianaran Danish Shahzad Atanas Poibrenski Christian Müller P. Slusallek NoLa 38 3 0 27 Apr 2024
Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection Chang-rui Liu Weiming Zhang Xiangru Lin Wei Zhang Xiao Tan Junyu Han Xiaomao Li Errui Ding Jingdong Wang 49 33 0 27 Mar 2023
SVFormer: Semi-supervised Video Transformer for Action Recognition Zhen Xing Qi Dai Hang-Rui Hu Jingjing Chen Zuxuan Wu Yu-Gang Jiang ViT 22 69 0 23 Nov 2022
Dense Teacher: Dense Pseudo-Labels for Semi-supervised Object Detection Hongyu Zhou Zheng Ge Songtao Liu Weixin Mao Zeming Li Haiyan Yu Jian‐Yuan Sun 11 87 0 06 Jul 2022
Omni-DETR: Omni-Supervised Object Detection with Transformers Pei Wang Zhaowei Cai Hao Yang Gurumurthy Swaminathan Nuno Vasconcelos Bernt Schiele Stefano Soatto 24 40 0 30 Mar 2022
How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs Hazel Doughty Cees G. M. Snoek 20 19 0 23 Mar 2022
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