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!
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]
Revisiting Pseudo-Label for Single-Positive Multi-Label Learning
Biao Liu, Ning Xu, Jiaqi Lv, Xin Geng.
ICML 2023 | [Paper]
Spatial Implicit Neural Representations for Global-Scale Species Mapping
Elijah Cole, Grant Van Horn, Christian Lange, Alexander Shepard, Patrick Leary, Pietro Perona, Scott Loarie, Oisin Mac Aodha.
ICML 2023 | [Paper]
Hierarchical Prompt Learning Using CLIP for Multi-label Classification with Single Positive Labels
Ao Wang, Hui Chen, Zijia Lin, Zixuan Ding, Pengzhang Liu, Yongjun Bao, Weipeng Yan, Guiguang Ding.
ACM MM 2023 | [Paper]
Semantic Contrastive Bootstrapping for Single-positive Multi-label Recognition
Cheng Chen, Yifan Zhao, Jia Li.
IJCV 2023 | [Paper] [Code]
Multi-Label Classification with Single Positive Label for Remote Sensing Image
Keigo Fujii; Akira Iwasaki.
IGARSS 2023 | [Paper]
Is one label all you need? Single positive multi-label training in medical image analysis
Helen Schneider, Priya Priya, David Biesner, Rebecca Kador, Yannik C. Layer, Maike Theis, Sebastian Nowak, Alois M. Sprinkart, Ulrike I. Attenberger, Rafet Sifa.
BigData 2024 | [Paper]
Vision-Language Pseudo-Labels for Single-Positive Multi-Label Learning
Xin Xing, Zhexiao Xiong, Abby Stylianou, Srikumar Sastry, Liyu Gong, Nathan Jacobs.
CVPRW 2024 | [Paper] [Code]
Prompt Expending for Single Positive Multi-Label Learning with Global Unannotated Categories
Zhongnian Li, Peng Ying, Meng Wei, Tongfeng Sun, Xinzheng Xu.
ICMR 2024 | [Paper] [Code]
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]
Can Class-Priors Help Single-Positive Multi-Label Learning?
Biao Liu, Jie Wang, Ning Xu, Xin Geng.
arXiv 2023 | [Paper]
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.
arXiv 2024 | [Paper]
Thanks to all the authors above for their great works!