Daniel McKee

I am a PhD student in Computer Science at the University of Illinois at Urbana-Champaign advised by Professor Svetlana Lazebnik. My research interests lie within computer vision, and I am especially interested in how we can learn video and multimodal models from limited annotations.

During internships, I've had the pleasure to collaborate with some fantastic mentors including Bryan Russell, Justin Salamon, and Josef Sivic this past year at Adobe, and Bing Shuai, Davide Modolo, and Joseph Tighe during previous years at Amazon.

Before coming to UIUC, I completed undergraduate degrees in Computer Science and Mathematics at Duke University.

Email / CV

Research Internships


A9.com

Amazon

Adobe
Palo Alto, CA | 2018 Seattle, WA | 2019-2021 San Jose, CA | 2022

Education


Duke University

University of Illinois at Urbana-Champaign
Durham, NC | 2013-2017 Urbana, IL | 2017-Present

Projects

StyleGAN knows Normal, Depth, Albedo, and More

Anand Bhattad, Daniel McKee, Derek Hoiem, David Forsyth

NeurIPS 2023
Project page | Paper

Language-Guided Music Recommendation for Video via Prompt Analogies

Daniel McKee, Justin Salamon, Josef Sivic, Bryan Russell

🌟 Highlight at CVPR 2023 🌟
Project page | Paper | Dataset

Robust Online Video Instance Segmentation with Track Queries

Zitong Zhan, Daniel McKee, Svetlana Lazebnik

ArXiv 2022
Project page | Paper | Code

Transfer of Representations to Video Label Propagation: Implementation Factors Matter

Daniel McKee, Zitong Zhan, Bing Shuai, Davide Modolo, Joseph Tighe, Svetlana Lazebnik

ArXiv 2022
Project page | Paper

Multi-Object Tracking with Hallucinated and Unlabeled Videos

Daniel McKee, Bing Shuai, Andrew Berneshawi, Manchen Wang, Davide Modolo, Svetlana Lazebnik, Joseph Tighe

CVPR 2021 LUV Workshop
Project page | Paper

Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing

Aiyu Cui, Daniel McKee, Svetlana Lazebnik

ICCV 2021
Best Paper at CVPR 2021 CVFAD Workshop
Project page | Paper | Code

Teaching