Meng Tang, University of Waterloo

Meng Tang

Assistant Professor (Since 2023)

Department of Computer Science and Engineering

University of California, Merced

Email: mtang4 AT ucmerced.edu

Office: SE2 279

I am interested in computer vision and machine learning, with particular focus on weak supervision.

I am looking for multiple fully funded PhD students. Send me your cv and transcript if you are interested!

I am also looking for visiting students!

GoogleScholar GitHub CV

Teaching

CSE 185 Introduction to Computer Vision, Fall 2023

PhD students

Fang Chen, since Fall 2023
Jieke Wang, since Fall 2023

Publication

Journals

Kernel Cuts: Kernel and Spectral Clustering meet Regularization

Meng Tang, Dmitrii Marin, Ismail Ben Ayed, Yuri Boykov

International Journal of Computer Vision (IJCV), volume 127, pages 477-511, May 2019. [PDF] [arXiv]
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]
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]
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, volume 6, pages 868-873, 2012. [PDF]

Conferences

Decepticon: Understanding Vulnerabilities of Transformers

Mujahid Al Rafi, Yuan Feng, Fan Yao, Meng Tang, Hyeran Jeon

IEEE International Symposium on Workload Characterization (IISWC), Ghent, Belgium, October 2023.
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), Seattle, USA, June 2020. [PDF] [Video]
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), Long Beach, USA, June 2019. [PDF] [Code]
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), Munich, Germany, September 2018. [PDF] [Slides] [Code] [arXiv]
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), Amsterdam, Netherlands, July 2018. [PDF] (oral)
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), Salt Lake City, USA, June 2018. [PDF] [Poster]
Normalized Cut Meets MRF

Meng Tang, Dmitrii Marin, Ismail Ben Ayed, Yuri Boykov

European Conference on Computer Vision (ECCV), Amsterdam, the Netherlands, October 2016. [PDF] [Code] [Poster] [Slides] [Video](oral)
Secrets of GrabCut and Kernel K-means

Meng Tang, Ismail Ben Ayed, Dmitrii Marin, Yuri Boykov

IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015. [PDF] [Code] [Poster]
Pseudo-Bound Optimization for Binary Energies

Meng Tang, Ismail Ben Ayed, Yuri Boykov

European Conference on Computer Vision (ECCV), Zurich, Switzerland, September 2014. [PDF] [Code] [Poster] [Slides] [Video](oral)
GrabCut in One Cut

Meng Tang, Lena Gorelick, Olga Veksler, Yuri Boykov

IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, December 2013. [PDF] [Code] [Poster]

Workshops

Latent Space Editing in Transformer-Based Flow Matching

Tao Hu, David W Zhang, Pascal Mettes, Meng Tang, Deli Zhao, Cees G.M. Snoek

Workshop on New Frontiers in Learning, Control, and Dynamical Systems at the International Conference on Machine Learning (ICML-W),

Honolulu, Hawaii, USA, 2023. [PDF] [Code] [Poster]