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 efficient training and inference and autonomous driving.

Papers

Mengtian Li, Yuxiong Wang and Deva Ramanan. Towards Streaming Image Understanding. In ECCV, 2020.

Oral Presentation (2%)

[Project page] [Paper] [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

I wrote a python-HTML-javascript tool for computer vision research. Might be really handy for visualizing datasets, comparing algorithms and making figures for papers!