Mengtian (Martin) Li

Ph.D. Student, CMU RI

Smith Hall 224

Email: mtli [at] cs [dot] cmu [dot] edu

I am a Ph.D. student (2017-) at the Robotics Insitute of Carnegie Mellon University, where I am fortunate to work with Deva Ramanan. Previously, I was a master student at the same institute, advised by Daniel Huber. I received my B.S. from Kuang Yaming Honors School of Nanjing University.

My research interest is in computer vision and machine learning. In particular, I am interested in resource-constrained learning and inference.

News

Apr 2021 Invited talk at Georgia Tech RoboGrads Seminar
Mar 2021 Guest lecture at UIUC Advanced Computer Vision course
Feb 2021 Announcing the Streaming Perception Challenge (CVPR 2021)!
Oct 2020 Invited talk at Uber ATG
Aug 2020 Won the ECCV Best Paper Honorable Mention Award!
Apr 2020 Invited talk at Aurora

Papers

Mengtian Li, Yu-Xiong Wang and Deva Ramanan. Towards Streaming Perception. In ECCV, 2020.

Best Paper Honorable Mention

[Project page + talk + data] [Paper] [Code] [Bibtex]

Mengtian Li, Ersin Yumer and Deva Ramanan. Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints. In ICLR, 2020.

[Project page] [Paper] [Talk] [Code] [Bibtex]

Mengtian Li, Zhe Lin, Radomír Měch, Ersin Yumer and Deva Ramanan. Photo-Sketching: Inferring Contour Drawings from Images. In WACV, 2019.

[Project page] [Paper] [Code] [Bibtex]

Mengtian Li, Laszlo Jeni, Deva Ramanan. Brute-Force Facial Landmark Analysis with a 140,000-Way Classifier. In AAAI, 2018.

[Paper] [Code] [Bibtex]

Mengtian Li, Daniel Huber. Guaranteed Parameter Estimation for Discrete Energy Minimization. In WACV, 2017.

[Paper] [Bibtex]

Mengtian Li, Alexander Shekhovtsov, Daniel Huber. Complexity of Discrete Energy Minimization Problems In ECCV, 2016.

Spotlight Presentation

[Paper] [Poster] [Talk] [Bibtex]

Misc

Confucius (孔子) once said: “if a craftsman wants to do good work, he must first sharpen his tools (工欲善其事，必先利其器).” I find that this concept also applies to research. Over the years, I have created various tools related to my research and I have some of them open sourced on Github:

  • HTML4Vision: a python-HTML-javascript tool for visualizing datasets, comparing algorithms and making figures
  • MTCMon: a web-based cluster resource monitor (widely adopted at CMU RI)
  • parscript: utilities for parallel or distributed execution of jobs