Self-Supervised GANs via Auxiliary Rotation Loss

Chen, Ting, Zhai, Xiaohua, Ritter, Marvin, Lucic, Mario, Houlsby, Neil·2019·2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Cited by (323)

Items 201–300 of 323

  1. Physics-Informed Machine Learning Model Generalization in AIoT: Opportunites and Challenges
    Rui Tan, Wenjie Luo · 2023 · Cyber-Physical Systems and Internet of Things Week (CPS-IoT Week)
  2. Unpaired Image-to-Image Translation with Limited Data to Reveal Subtle Phenotypes
    Anis Bourou, Kévin Daupin, Véronique Dubreuil, Aurélie de Thonel, Valérie Mezger, Auguste Genovesio · 2023 · IEEE International Symposium on Biomedical Imaging (ISBI)
  3. Domain and label efficient approach for diabetic retinopathy severity detection
    Kriti Ohri, Mukesh Kumar · 2023 · Multimedia Tools and Applications
  4. FedLID: Self-Supervised Federated Learning for Leveraging Limited Image Data
    Athanasios Psaltis, Anestis Kastellos, Charalampos Z. Patrikakis, Petros Daras · 2023 · IEEE International Conference on Computer Vision Workshops
  5. SelfSphNet: Motion Estimation of a Spherical Camera via Self-Supervised Learning
    Dabae Kim, Sarthak Pathak, Alessandro Moro, Atsushi Yamashita, Hajime Asama · 2020 · IEEE Access
  6. SSC-GAN: A Novel GAN Based on the Same Solution Constraints of First-Order ODEs
    Hongyou Chen, Fan Chen, Hongjie He · 2021 · International Journal of Pattern Recognition and Artificial Intelligence
  7. Attention regularized semi-supervised learning with class-ambiguous data for image classification
    Xiaoyang Huo, Xiangping Zeng, Si Wu, Hau−San Wong · 2022 · Pattern Recognition
  8. Domain-Agnostic Contrastive Representations for Learning from Label Proportions
    Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, B. Ravindran, Aravindan Raghuveer · 2022 · International Conference on Information and Knowledge Management
  9. Üretken Yapay Zekâ
    Melisa Gozet, Ulaş Filiz, Asım Egemen Yılmaz · 2023 · International Journal of Multidisciplinary Studies and Innovative Technologies
  10. Countering Noisy Labels By Learning From Auxiliary Clean Labels
    Tsung Wei Tsai, Chongxuan Li, Jun Zhu · 2019 · arXiv (Cornell University)
  11. Dual Contrastive Loss and Attention for GANs
    Ning Yu, Guilin Liu, Ayşegül Dündar, Andrew Tao, Bryan Catanzaro, Larry Steven Davis, Mario Fritz · 2021 · arXiv (Cornell University)
  12. Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions
    Huangjie Zheng, Mingyuan Zhou · 2020 · arXiv (Cornell University)
  13. Discriminative-Generative Representation Learning for One-Class Anomaly Detection
    Xuan Xia, Xizhou Pan, He, Xing, Jingfei Zhang, Ning Ding, Lin Ma · 2021 · arXiv (Cornell University)
  14. Correlation-Based Knowledge Distillation in Exemplar-Free Class-Incremental Learning
    Zijian Gao, Bo Liu, Kele Xu, Xinjun Mao, Huaimin Wang · 2025 · IEEE Open Journal of the Computer Society
  15. Rethinking Obscured Sub-Optimality in Analytic Learning for Exemplar-Free Class-Incremental Learning
    Zijian Gao, Kele Xu, Xingxing Zhang, Huiping Zhuang, Tianjiao Wan, Bo Ding, Xinjun Mao, Huaimin Wang · 2025 · IEEE Transactions on Circuits and Systems for Video Technology
  16. A survey on design choices for self-supervised learning in computer vision
    Ladyna Wittscher · 2026 · Artificial Intelligence Review
  17. Exploring Intra-class Variation Factors with Learnable Cluster Prompts for Semi-supervised Image Synthesis
    Yunfei Zhang, Xiaoyang Huo, Tianyi Chen, Si Wu, Hau−San Wong · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  18. Generative adversarial networks via a composite annealing of noise and diffusion
    Kensuke Nakamura, Simon Korman, Byung‐Woo Hong · 2023 · Pattern Recognition
  19. Any region can be perceived equally and effectively on rotation pretext task using full rotation and weighted-region mixture
    Wei Dai, Tianyi Wu, Rui Liu, Min Wang, Jun Liu, Jun Liu · 2024 · Neural Networks
  20. FDPNet: Deep forgery detection by leveraging multi-scale self-forgery images generating
    Boyang Li, Huihuang Zhao, Leyi Li · 2025 · The Journal of Supercomputing
  21. NoiseTransfer: Image Noise Generation with Contrastive Embeddings
    Seunghwan Lee, Tae Hyun Kim · 2023 · Lecture notes in computer science
  22. MAPConNet: Self-supervised 3D Pose Transfer with Mesh and Point Contrastive Learning
    Jiaze Sun, Zhixiang Chen, Tae‐Kyun Kim · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
  23. DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta
    Yan Hong, Li Niu, Jianfu Zhang, Liqing Zhang · 2022 · arXiv (Cornell University)
  24. How Adversarial REM Dreams May Facilitate Creativity, and Why We Become Aware of Them
    Deperrois, Nicolas, Petrovici, Mihai, Jordan, Jakob, Huber, Lukas, Senn, Walter · 2024 · Clinical and Translational Neuroscience
  25. Enhanced self-supervised GANs with blend ratio classification
    Qinyu Zhou, Jianwei Zhang, Guoqiang Han, Zhihui Ruan, Ying Wei · 2022 · Multimedia Tools and Applications
  26. A U-Net based Self-Supervised Image Generation Model Applying PCA using Small Datasets
    Sang Hun Han, Asim Niaz, Kwang Nam Choi · 2023 · Asia Conference on Algorithms, Computing and Machine Learning (CACML)
  27. POA: Pre-training Once for Models of All Sizes
    Yingying Zhang, Xin Guo, Jiangwei Lao, Lei Yu, Lixiang Ru, Jian Wang, Guo Ye, Huimei He, Jingdong Chen, Ming Yang · 2024 · Lecture notes in computer science
  28. Exploring the spatial reasoning ability of neural models in human IQ tests
    Hyunjae Kim, Yookyung Koh, Jinheon Baek, Jaewoo Kang · 2021 · Neural Networks
  29. Generative Data Augmentation Guided by Triplet Loss for Speech Emotion Recognition
    Shijun Wang, Hamed Hemati, Jón Guðnason, Damian Borth · 2022 · Interspeech (USB)
  30. GH-Feat: Learning Versatile Generative Hierarchical Features From GANs
    Yinghao Xu, Yujun Shen, Jiapeng Zhu, Ceyuan Yang, Bolei Zhou · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
  31. Shuffle is What You Need
    Wan Lin, Lantian Li, Dong Wang · 2022 · International Symposium on Chinese Spoken Language Processing (ISCSLP)
  32. Regularizing Label-Augmented Generative Adversarial Networks Under Limited Data
    Liang Hou · 2023 · IEEE Access
  33. Topic-Aware Contrastive Learning and K-Nearest Neighbor Mechanism for Stance Detection
    Yepeng Sun, Jicang Lu, Ling Wang, Shunhang Li, Ningbo Huang · 2023 · ACM International Conference on Information and Knowledge Management (CIKM)
  34. MHAiR: A Dataset of Audio-Image Representations for Multimodal Human Actions
    Muhammad Bilal Shaikh, Douglas Chai, Syed Mohammed Shamsul Islam, Naveed Akhtar · 2024 · Data
  35. Boosting Fashion Image Attributes Classification Performance with MT-GAN Training Technique
    Qun Li, Changbo Hu, Keng-hao Chang, Ruofei Zhang · 2020 · IEEE International Conference on Data Science and Advanced Analytics (DSAA)
  36. Structure-aware unsupervised tagged-to-cine MRI synthesis with self disentanglement
    Xiaofeng Liu, Fangxu Xing, Jerry L. Prince, Maureen L. Stone, Georges El Fakhri, Jonghye Woo · 2022 · SPIE Medical Imaging: Image Processing
  37. Improving Cancer Metastasis Detection via Effective Contrastive Learning
    Haixia Zheng, Zhou Yu, Xin Huang · 2022 · Mathematics
  38. Unsupervised Controllable Generation with Self-Training
    Grigorios G. Chrysos, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar · 2021 · International Joint Conference on Neural Networks (IJCNN)
  39. Exploring the diversity and invariance in yourself for visual pre-training task
    Longhui Wei, Lingxi Xie, Wengang Zhou, Houqiang Li, Qi Chuan Tian · 2023 · Pattern Recognition
  40. A simple baseline for domain adaptation using rotation prediction
    Ajinkya Tejankar, Hamed Pirsiavash · 2019 · arXiv (Cornell University)
  41. Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects
    Juil Sock, Pedro Castro, Anil Armagan, Guillermo Garcia-Hernando, Tae‐Kyun Kim · 2020 · arXiv (Cornell University)
  42. Towards Self-learning Edge Intelligence in 6G
    Yong Xiao, Guangming Shi, Yingyu Li, Walid Saad, H. Vincent Poor · 2020 · arXiv (Cornell University)
  43. BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer
    Or Patashnik, Dov Danon, Hao Zhang, Daniel Cohen‐Or · 2020 · arXiv (Cornell University)
  44. Dual Contradistinctive Generative Autoencoder
    Gaurav Parmar, Dacheng Li, Kwonjoon Lee, Zhuowen Tu A · 2020 · arXiv (Cornell University)
  45. Adaptive Weighted Discriminator for Training Generative Adversarial Networks
    Vasily Zadorozhnyy, Qiang Shawn Cheng, Qiang Ye · 2020 · arXiv (Cornell University)
  46. cGANs with Auxiliary Discriminative Classifier.
    Liang Hou, Qi Cao, Huawei Shen, Xueqi Cheng · 2021 · arXiv (Cornell University)
  47. Evolutionary Machine Learning Meets Self-Supervised Learning: A Comprehensive Survey
    Adriano Vinhas, João Correia, Penousal Machado · 2026 · IEEE Access
  48. Conditional Self-Supervised Learning for Few-Shot Learning
    Yuexuan An, Hui Xue, Xingyu Zhao · 2026 · IEEE Transactions on Circuits and Systems for Video Technology
  49. Self-Supervised Feature Enhancement: Applying Internal Pretext Task to Supervised Learning
    Tianshu Xie, Yuhang Yang, Zilin Ding, Xuan Cheng, Xiaomin Wang, Haigang Gong, Ming Liu · 2022 · IEEE Access
  50. Antinoise Learning and Coalitional Game GAN
    Hongyou Chen, Hongjie He, Fan Chen, Yiming Zhu · 2021 · International Journal of Pattern Recognition and Artificial Intelligence
  51. VCL-PL:Semi-Supervised Learning from Noisy Web Data with Variational Contrastive Learning
    Mehmet Can Yavuz, Berrin A. Yanikoglu · 2022 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
  52. Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data
    Kai Katsumata, Duc Minh Vo, Tatsuya Harada, Hideki Nakayama · 2024 · IEEE Winter Conference on Applications of Computer Vision
  53. Weakly-Supervised Representation Learning for Video Alignment and Analysis
    Guy Bar-Shalom, George Leifman, Michael Elad · 2024 · IEEE Winter Conference on Applications of Computer Vision
  54. Anomaly classification based on self-supervised learning and its application
    Yongsheng Han, Zhiquan Qi, Yingjie Tian · 2024 · Journal of Radiation Research and Applied Sciences
  55. Noise Homogenization via Multi-Channel Wavelet Filtering for High-Fidelity Sample Generation in Gans
    Shaoning Zeng, Bob Zhang · 2021 · IEEE International Conference on Multimedia and Expo (ICME)
  56. Don’t miss the mismatch: investigating the objective function mismatch for unsupervised representation learning
    Bonifaz Stuhr, Jürgen Brauer · 2022 · Neural Computing and Applications
  57. Multi-penalty Functions GANs via Multi-task Learning
    Hongyou Chen, Hongjie He, Fan Chen · 2021 · Lecture notes in computer science
  58. Generative imaging and image processing via generative encoder
    Yong Zheng Ong, Haizhao Yang · 2021 · Inverse Problems and Imaging
  59. GIAD-ST: Detecting anomalies in human monitoring based on generative inpainting via self-supervised multi-task learning
    Ning Dong, Einoshin Suzuki · 2022 · Journal of Intelligent Information Systems
  60. Self-supervised Weighted Hashing with Topology Mining
    Peishuo Li, Pandeng Li, Wanting Yin · 2023 · International Conference on Control Engineering and Artificial Intelligence (CCEAI)
  61. SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation
    Kunal Chaturvedi, Ali Braytee, Jun Li, Mukesh Prasad · 2023 · Sensors
  62. PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style Translation
    Zexi Chen, Jiaxin Guo, Xuecheng Xu, Yunkai Wang, Huang Huang, Yue Wang, Rong Xiong · 2021 · IEEE Robotics and Automation Letters
  63. Generative Adversarial Data Programming
    Arghya Pal, Vineeth Nallure Balasubramanian · 2020 · arXiv (Cornell University)
  64. Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
    Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael C. Mozer, Philippe Beaudoin, Yoshua Bengio · 2020 · arXiv (Cornell University)
  65. Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering
    Boaz Lerner, Guy Shiran, Daphna Weinshall · 2020 · arXiv (Cornell University)
  66. GMM-Based Generative Adversarial Encoder Learning
    Yuri Feigin, Hedva Spitzer, Raja Giryes · 2020 · arXiv (Cornell University)
  67. Are High-Frequency Components Beneficial for Training of Generative Adversarial Networks.
    Ziqiang Li, Pengfei Xia, Rui Xue, Yanghui Hu, Bin Li · 2021 · arXiv (Cornell University)
  68. Why Adopting Regularization and Normalization For Generative Adversarial Networks: A Survey
    Ziqiang Li, Xintian Wu, Rentuo Tao, Pengfei Xia, Huanhuan Chen, Bin Li · 2020 · arXiv (Cornell University)
  69. How Adversarial Rem-Dreams May Facilitate Creativity, and Why We Become Aware of Them
    Nicolas Deperrois, Mihai Alexandru Petrovici, Jakob Jordan, Lukas S. Huber, Walter Senn · 2024 · Preprints.org
  70. Self-Supervised Learning for Ultrasound Probe Angle Prediction in Plantar Fascia Images
    Benjamin W. Roop, Kevin J. Brady, Lars Gjesteby, Brian S. Baum, Laura J. Brattain · 2023 · Wearable and Implantable Body Sensor Networks
  71. MSDGAN: Multi-Scale Dilated Generative Adversarial Network for Smoke Removal and Image Restoration
    K. M. Gwak, Young J. Rho · 2024
  72. An analytical review of GANs: technical evolution, architectures, applications, datasets, and challenges
    Sondos Ardebili, Masoud Kargar, Nayer Seyed Hoseini · 2026 · Iran Journal of Computer Science
  73. Reframing control methods for parameters optimization in adversarial image generation
    Qamar Alfalouji, Piergiorgio Sartor, Pietro Zanuttigh · 2022 · Neural Networks
  74. Enhancing Representation Learning with Deep Classifiers in Presence of Shortcut
    Amirhossein Ahmadian, Fredrik Lindsten · 2023 · IEEE International Conference on Acoustics Speech and Signal Processing
  75. A Relational Instance-Based Clustering Method with Contrastive Learning for Open Relation Extraction
    Xiaoge Li, D. Guo, Tiantian Wang · 2023 · Lecture notes in computer science
  76. Self-supervised Learning for 3D CT Scan Segmentation
    Bingquan Shen, Yew Keng Timothy Low · 2023 · Springer eBooks
  77. IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature Representation
    Sonal Kumar, Anirudh Phukan, Arijit Sur · 2024 · IEEE International Conference on Acoustics Speech and Signal Processing
  78. Label Augmentation as Inter-class Data Augmentation for Conditional Image Synthesis with Imbalanced Data
    Kai Katsumata, Duc Minh Vo, Hideki Nakayama · 2024 · IEEE Winter Conference on Applications of Computer Vision
  79. Robust Semantic Segmentation for Street Fashion Photos
    Anh H. Dang, Wataru Kameyama · 2020 · International Conference on Advanced Communication Technology
  80. Conditional Adversarial Camera Model Anonymization
    Jerone T. A. Andrews, Yidan Zhang, Lewis D. Griffin · 2020 · Lecture notes in computer science
  81. Pose Randomization for Weakly Paired Image Style Translation.
    Zexi Chen, Jiaxin Guo, Xuecheng Xu, Yunkai Wang, Yue Wang, Rong Xiong · 2020 · arXiv (Cornell University)
  82. Direct Adversarial Training: A New Approach for Stabilizing The Training Process of GANs
    Ziqiang Li, Pengfei Xia, Rentuo Tao, Hongjing Niu, Bin Li · 2020 · arXiv (Cornell University)
  83. The emergence of visual semantics through communication games
    Daniela Mihai, Jonathon S. Hare · 2021 · arXiv (Cornell University)
  84. Self-supervision of Feature Transformation for Further Improving Supervised Learning
    Zilin Ding, Yuhang Yang, Xuan Cheng, Xiaomin Wang, Ming Liu · 2021 · arXiv (Cornell University)
  85. Temporal Knowledge Consistency for Unsupervised Visual Representation Learning
    Weixin Feng, Yuanjiang Wang, Lihua Ma, Ye Yuan, Zhang, Chi · 2021 · arXiv (Cornell University)
  86. How Rapid-Eye-Movement Dreams May Facilitate Learning and Creativity
    Nicolas Deperrois, Mihai Alexandru Petrovici, Jakob Jordan, Lukas S. Huber, Walter Senn · 2024 · Preprints.org
  87. A Multi-view Perspective of Self-supervised Learning
    Chuanxing Geng, Zhenghao Tan, Songcan Chen · 2020 · arXiv (Cornell University)
  88. Multi-scale Deep CNN Network for Unsupervised Monocular Depth Estimation
    Yingcai Wan, Lijing Fang, Zhao Qiankun · 2019 · IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems
  89. Pseudo Conditional Regularization for Inverse Mapping of GANs
    Sang-Heon Shim, Jae‐Pil Heo · 2020 · IEEE Access
  90. Self-Supervised Visual Attention Learning for Vehicle Re-Identification.
    Ming Li, Yiming Zhao, Yecheng Lyu, Ziming Zhang · 2020 · arXiv (Cornell University)
  91. Latent Space Conditioning on Generative Adversarial Networks
    Ricard Durall, Kalun Ho, Franz‐Josef Pfreundt, Janis Keuper · 2021 · International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP)
  92. Discovering Discriminative Geometric Features with Self-Supervised Attention for Vehicle Re-Identification and Beyond.
    Ming Li, Xinming Huang, Ziming Zhang · 2020 · arXiv (Cornell University)
  93. Label Geometry Aware Discriminator for Conditional Generative Networks
    Sapkota, Suman, Bidur Khanal, Binod Bhattarai, Bishesh Khanal, Tae‐Kyun Kim · 2021 · arXiv (Cornell University)
  94. Regularization and Normalization For Generative Adversarial Networks: A Survey
    Ziqiang Li, Rentuo Tao, Pengfei Xia, Huanhuan Chen, Bin Li · 2020 · arXiv (Cornell University)
  95. OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
    Spyros Gidaris, Andrei Bursuc, Gilles Puy, Nikos Komodakis A, Matthieu Cord, Patrick Pérez · 2020 · arXiv (Cornell University)
  96. ScaleNet: An Unsupervised Representation Learning Method for Limited Information
    Hui-Li Huang, Max Mahdi Roozbahani · 2023 · German Conference on Pattern Recognition
  97. Self-supervised learning with consistency loss for improving GANs
    Jie Gao, Dandan Song · 2022 · International Conference on Mechanisms and Robotics (ICMAR)
  98. Label Geometry Aware Discriminator for Conditional Generative Adversarial Networks
    Suman Sapkota, Bidur Khanal, Binod Bhattarai, Bishesh Khanal, Tae‐Kyun Kim · 2022 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
  99. RIS-GAN: Self-Supervised GANs via Recovering Initial State of Subimages
    Ying Wei, Jianwei Zhang, Longqi Zhong · 2022 · Pattern Recognition Letters
  100. Generating New Arabic Letters-Rawashin Design using GAN
    Rufaidah A. Bagido · 2022 · National Computing Colleges Conference (NCCC)