Awesome Single Positive Multi-Label Learning 
This is a collection of papers and code for single positive multi-label learning (SPML), an interesting and challenging variant of multi-label learning.
Feel free to create pull requests (e.g., add missing papers, correct errors) if there are anything that can make this community better!
Table of Contents
Published Papers
Multi-Label Learning from Single Positive Labels
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul, Pietro Perona, Dan Morris, Nebojsa Jojic.
CVPR 2021 | [Paper] [Code]
Large Loss Matters in Weakly Supervised Multi-Label Classification
Youngwook Kim, Jae Myung Kim, Zeynep Akata, Jungwoo Lee.
CVPR 2022 | [Paper] [Code]
Acknowledging the Unknown for Multi-label Learning with Single Positive Labels
Donghao Zhou, Pengfei Chen, Qiong Wang, Guangyong Chen, Pheng-Ann Heng.
ECCV 2022 | [Paper] [Code]
Hyperspherical Learning in Multi-Label Classification
Bo Ke, Yunquan Zhu, Mengtian Li, Xiujun Shu, Ruizhi Qiao, Bo Ren.
ECCV 2022 | [Paper] [Code]
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification
Rabab Abdelfattah, Xin Zhang, Zhenyao Wu, Xinyi Wu, Xiaofeng Wang, Song Wang.
ECCVW 2022 | [Paper]
G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification
Rabab Abdelfattah, Xin Zhang, Mostafa M. Fouda, Xiaofeng Wang, Song Wang.
BMVC 2022 | [Paper]
An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition
Kiyoon Kim, Davide Moltisanti, Oisin Mac Aodha, Laura Sevilla-Lara.
BMVC 2022 | [Paper] [Code]
One Positive Label is Sufficient: Single-Positive Multi-Label Learning with Label Enhancement
Ning Xu, Congyu Qiao, Jiaqi Lv, Xin Geng, Min-Ling Zhang.
NeurIPS 2022 | [Paper] [Code]
Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels
Ming-Kun Xie, Jia-Hao Xiao, Sheng-Jun Huang.
NeurIPS 2022 | [Paper] [Code]
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations
Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman.
WACV 2023 | [Paper]
Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification
Youngwook Kim, Jae Myung Kim, Jieun Jeong, Cordelia Schmid, Zeynep Akata, and Jungwoo Lee.
CVPR 2023 | [Paper] [Code]
Exploring Structured Semantic Prior for Multi Label Recognition with Incomplete Labels
Zixuan Ding, Ao Wang, Hui Chen, Qiang Zhang, Pengzhang Liu, Yongjun Bao, Weipeng Yan, Jungong Han.
CVPR 2023 | [Paper] [Code]
Understanding Label Bias in Single Positive Multi-Label Learning
Julio Arroyo, Pietro Perona, Elijah Cole.
Tiny Papers @ ICLR 2023 | [Paper]
Pseudo Labels for Single Positive Multi-Label Learning
Julio Arroyo.
Tiny Papers @ ICLR 2023 | [Paper]
Archives
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Youcai Zhang, Yuhao Cheng, Xinyu Huang, Fei Wen, Rui Feng, Yaqian Li, Yandong Guo.
arXiv 2022 | [Paper] [Code]
A Patch-Based Architecture for Multi-label Classification from Single Label Annotations
Warren Jouanneau, Aurélie Bugeau, Marc Palyart, Nicolas Papadakis, Laurent Vézard.
arXiv 2022 | [Paper]
An Effective Approach for Multi-label Classification with Missing Labels
Xin Zhang, Rabab Abdelfattah, Yuqi Song, Xiaofeng Wang.
arXiv 2022 | [Paper]
Leveraged Asymmetric Loss with Disambiguation for Multi-label Recognition with One-Positive Annotations
Jingyi Cui, Tao Huang, Hanyuan Hang, Yisen Wang, James Kwok.
OpenReview 2022 | [Paper]
Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels
Xiang Li*, Xinrui Wang*, Songcan Chen.
arXiv 2023 | [Paper]
Global-Scale Species Mapping From Crowdsourced Data
Elijah Cole, Grant Van Horn, Alexander Shepard, Patrick Leary, Scott Loarie, Pietro Perona, Oisin Mac Aodha.
OpenReview 2023 | [Paper]
Semantic Contrastive Bootstrapping for Single-positive Multi-label Recognition
Cheng Chen, Yifan Zhao, Jia Li.
arXiv 2023 | [Paper] [Code]
Acknowledgements
Thanks to all the authors above for their great works!