| CARVIEW |
Select Language
HTTP/2 200
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Mon, 20 Nov 2023 04:16:47 GMT
access-control-allow-origin: *
etag: W/"655addaf-1b3f"
expires: Mon, 29 Dec 2025 18:57:15 GMT
cache-control: max-age=600
content-encoding: gzip
x-proxy-cache: MISS
x-github-request-id: B683:2685F2:921B1C:A40671:6952CCB2
accept-ranges: bytes
age: 0
date: Mon, 29 Dec 2025 18:47:15 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210090-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767034035.974084,VS0,VE226
vary: Accept-Encoding
x-fastly-request-id: 5d8346ff655365ad088e3ddcc28db7cca3e8b5e4
content-length: 2305
Junwen Chen
About Me
I am a Ph.D candidate in the Department of Computer Science and Engineering at Michigan State University, advised by Dr. Yu Kong.
My research interests are computer vision, multi-modality, and trustworthy AI motivated by real-world problems in surveillence, sports, social media, and healthcare.
Specifically, my research focuses on the topics of long-form video understanding, human behavior modeling, and visual grounding. I developed predictive methods to capture spatio-temporal, dynamic, and interpretable patterns in large-scale multi-modal data.
Contact: chenjunw at msu dot edu
Research Interests
- Multi-modality
- Video understanding
- Trustworthy AI in computer vision
News
| 07.2023 | Paper on long-form VideoQA was accepted by ACM Multimedia 2023. |
| 08.2022 | Passed comprehensive exam. |
| 04.2023 | To present in CVPR'23 Doctoral Consortium. |
| 08.2022 | First day at MSU. |
| 02.2022 | Paper on online action detection was accepted by CVPR 2022. |
Professional Service
- Program Committee: IJCAI 2023
- Reviewer: CVPR 2021-2023
- Reviewer: ECCV 2022
- Reviewer: ICCV 2021