Fabien Delattre

I am a 3rd year Ph.D. student at the Manning College of Information & Computer Sciences at the University of Massachusetts Amherst. I am advised by Prof. Erik Learned-Miller and part of the Vision lab. I received a M.S. in Computer Sciences from ISEN Lille engineering school (2019) in France.

In the past, I interned at Mitsubishi Electric Research Laboratories (MERL), Samsung Strategy and Innovation Center (SSIC) and Thales.

CV / LinkedIn

Research

I'm interested in computer vision and machine learning. My current research is about motion perception.

Robust frame-to-frame camera rotation estimation in crowded scenes

Fabien Delattre, David Dirnfeld, Phat Nguyen, Stephen Scarano, Michael J. Jones, Pedro Miraldo, Erik Learned-Miller.

International Conference on Computer Vision (ICCV), 10 pages, 2023

project page / paper / code / data

A domain-agnostic approach for characterization of lifelong learning systems

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sebastien M. R. Arnold, Ese Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, David Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha.

Neural Networks, Volume 160, 70 pages, 2023

paper

C-14: assured timestamps for drone videos

Zhipeng Tang, Fabien Delattre, Pia Bideau, Mark Corner, Erik Learned-Miller

MobiCom, 2020

paper / code

Class projects

Minimum commitment Loss for Semantic Segmentation with partial labels

Fabien Delattre, Vishnu Balakrishnan

2020

paper

Self-supervised visual feature learning with curriculum

Vishal Keshav, Fabien Delattre

2020

paper / code

Tools

PaperMap is a literature review tool to build a citation graph, and see how papers relate to each other at a glance.

Teaching Assistantship

Fall 2020 - COMPSCI 250: Introduction to Computation
Spring 2021 - COMPSCI 230: Computer systems principles
Fall 2022 - COMPSCI 230: Computer systems principles
Spring 2023 - CMPSCI 574/674: Intelligent Visual Computing: A Neural Network Approach

Template from Jon Barron's website