Meng Tang

5. Self-Cross Diffusion Guidance for Text-to-Image Synthesis of Similar Subjects
   Weimin Qiu, Jieke Wang, Meng Tang
   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025. [PDF][Code][Prject Page]
6. ReDistill: Residual Encoded Distillation for Peak Memory Reduction of CNN
   Fang Chen, Gourav Datta, Mujahid Al Rafi, Hyeran Jeon, Meng Tang
   Transactions on Machine Learning Research (TMLR), 2025. [arxiv] [Code] [PDF]
7. Training Class-Imbalanced Diffusion Model Via Overlap Optimization
   Divin Yan, Lu Qi, Vincent Tao Hu, Ming-Hsuan Yang, Meng Tang
   arXiv preprint 2402.10821, Feb. 2024. [PDF]
8. ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic Segmentation
   Jacob Schnell, Jieke Wang, Lu Qi, Vincent Tao Hu, Meng Tang
   Workshop on SyntaGen at IEEE Conference on Computer Vision and Pattern Recognition (CVPR-W), 2024. [PDF][Code]
9. Latent Space Editing in Transformer-Based Flow Matching
   Vincent Tao Hu, David W Zhang, Pascal Mettes, Meng Tang, Deli Zhao, Cees G.M. Snoek
   Annual AAAI Conference on Artificial Intelligence (AAAI), 2024. [PDF] [Code]  [Poster]
10. Decepticon: Understanding Vulnerabilities of Transformers
    Mujahid Al Rafi, Yuan Feng, Fan Yao, Meng Tang, Hyeran Jeon
    IEEE International Symposium on Workload Characterization (IISWC), 2023. [PDF]
11. FroDO: From Detections to 3D Objects
    M. Rünz, K. Li, M. Tang, L. Ma, C. Kong, T. Schmidt, I. Reid, L. Agapito, J. Straub, S. Lovegrove, R. Newcombe
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [PDF] [Video]
12. Beyond Gradient Descent for Regularized Segmentation Losses
    Dmitrii Marin, Meng Tang, Ismail Ben Ayed, Yuri Boykov
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF] [Code]
13. Kernel Cuts: Kernel and Spectral Clustering meet Regularization
    Meng Tang, Dmitrii Marin, Ismail Ben Ayed, Yuri Boykov
    International Journal of Computer Vision (IJCV), 2019. [PDF] [arXiv]
14. Constrained-CNN losses for weakly supervised segmentation
    Hoel Kervadec, Jose Dolz, Meng Tang, Eric Granger, Yuri Boykov, Ismail Ben Ayed
    Medical Image Analysis (MedIA), 2019. [PDF] [Code] [MIDL 2018 version]
15. On Regularized Losses for Weakly-supervised CNN Segmentation
    Meng Tang, Federico Perazzi, Abdelaziz Djelouah, Ismail Ben Ayed, Christopher Schroers, Yuri Boykov
    European Conference on Computer Vision (ECCV), 2018. [PDF] [Slides] [Code] [arXiv]
16. Size-constraint loss for weakly supervised cnn segmentation
    Hoel Kervadec, Jose Dolz, Meng Tang, Eric Granger, Yuri Boykov, Ismail Ben Ayed
    Medical Imaging with Deep Learning (MIDL), 2018. [PDF] (oral)
17. Normalized Cut Loss for Weakly-supervised CNN Segmentation
    Meng Tang, Abdelaziz Djelouah, Federico Perazzi, Yuri Boykov, Christopher Schroers
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF] [Poster]
18. Kernel Clustering: Density Biases and Solutions
    Dmitrii Marin, Meng Tang, Ismail Ben Ayed, Yuri Boykov
    IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2017. [PDF]
19. Normalized Cut Meets MRF
    Meng Tang, Dmitrii Marin, Ismail Ben Ayed, Yuri Boykov
    European Conference on Computer Vision (ECCV), 2016. [PDF] [Code] [Poster] [Slides] [Video](oral)
20. Secrets of GrabCut and Kernel K-means
    Meng Tang, Ismail Ben Ayed, Dmitrii Marin, Yuri Boykov
    IEEE International Conference on Computer Vision (ICCV), 2015. [PDF] [Code] [Poster]
21. Pseudo-Bound Optimization for Binary Energies
    Meng Tang, Ismail Ben Ayed, Yuri Boykov
    European Conference on Computer Vision (ECCV), 2014. [PDF] [Code] [Poster] [Slides] [Video](oral)
22. GrabCut in One Cut
    Meng Tang, Lena Gorelick, Olga Veksler, Yuri Boykov
    IEEE International Conference on Computer Vision (ICCV), 2013. [PDF] [Code] [Poster]
23. Improved delay-range-dependent stability criteria for linear systems with interval time-varying delays
    Meng Tang, Yan-Wu Wang, Changyun Wen
    IET Control Theory & Applications, 2012. [PDF]