Gedas Bertasius
Assistant Professor
I am an Assistant Professor in the Computer Science department at the University of North Carolina, Chapel Hill. My research interests are in computer vision and machine learning. In particular, I'm interested in video understanding, human behavior modeling, and multi-modal deep learning. I'm also passionate about using computer vision for advanced sports analytics.
Research Overview
Video Recognition
Developing spatiotemporal models for automatic video analysis.
Virtual AI Assistants
Multimodal Learning
Building models that learn from video, audio, and text.
Computer Vision for Sports
Designing video-based AI models that can help people with various daily tasks.
Developing computer vision tools for advanced sports analytics.
Selected Projects
BIMBA: Selective-Scan Compression for Long-Range Video Question Answering
Md Mohaiminul Islam, Tushar Nagarajan, Huiyu Wang, Gedas Bertasius, Lorenzo Torresani
CVPR 2025 (1st Place Winner at CVPR 2025 Ego4D EgoSchema Challenge)
[arxiv] [project page] [code] [model] [demo] [bibtex]
BASKET: A Large-Scale Video Dataset for Fine-Grained Skill Estimation
Yulu Pan, Ce Zhang, Gedas Bertasius
CVPR 2025
[arxiv] [project page] [code] [data] [bibtex]
A Simple LLM Framework for Long-Range Video Question-Answering
Ce Zhang, Taixi Lu, Md Mohaiminul Islam, Ziyang Wang, Shoubin Yu, Mohit Bansal, Gedas Bertasius
EMNLP 2024
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani, Kris Kitani, Jitendra Malik, Gedas Bertasius, ... , Michael Wray
CVPR 2024
Video ReCap: Recursive Captioning of Hour-Long Videos
Md Mohaiminul Islam, Ngan Ho, Xitong Yang, Tushar Nagarajan, Lorenzo Torresani, Gedas Bertasius
CVPR 2024 (Egocentric Vision (EgoVis) Distinguished Paper Award)
[arxiv] [project website] [code] [dataset] [bibtex]
VindLU: A Recipe for Effective Video-and-Language Pretraining
Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, Gedas Bertasius
CVPR 2023
Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
ICML 2021
[arxiv] [code] [talk] [slides] [blog] [VentureBeat] [SiliconAngle] [bibtex]