Spatial Consistency Loss for Training Multi-Label Classifiers from
Single-Label Annotations

Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations

11 March 2022

Paul Kishan Rubenstein

Tinne Tuytelaars

Papers citing "Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations"

8 / 8 papers shown

Title
Boosting Single Positive Multi-label Classification with Generalized Robust Loss Yanxi Chen Chunxiao Li Xinyang Dai Jinhuan Li Weiyu Sun Yiming Wang Renyuan Zhang Tinghe Zhang Bo Wang 32 0 0 06 May 2024
Understanding Label Bias in Single Positive Multi-Label Learning Julio Arroyo Pietro Perona Elijah Cole 25 2 0 24 May 2023
Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning Ming-Kun Xie Jianxiong Xiao Hao-Zhe Liu Gang Niu Masashi Sugiyama Sheng-Jun Huang 40 16 0 04 May 2023
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition Kiyoon Kim Davide Moltisanti Oisin Mac Aodha Laura Sevilla-Lara 16 0 0 10 Oct 2022
A patch-based architecture for multi-label classification from single label annotations Warren Jouanneau Aurélie Bugeau Marc Palyart Nicolas Papadakis Laurent Vézard 28 0 0 14 Sep 2022
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 212 487 0 01 Oct 2021
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels Sangdoo Yun Seong Joon Oh Byeongho Heo Dongyoon Han Junsuk Choe Sanghyuk Chun 403 142 0 13 Jan 2021
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