Students and Faculty Attend Top AI Conference in New Orleans
Conference attendees listening to a presentation
Students and faculty from the Computer Science and Computer Engineering Department attended the 35th IEEE/CVF Computer Vision and Pattern Recognition Conference, which is the highest ranking conference in the field of artificial intelligence. Computer Science and Computer Engineering assistant professor and Computer Vision and Image Understanding Lab Director Khoa Luu joined his lab students in attending the conference June 19-24.
Luu and colleagues co-organized a workshop called "Precognition: Seeing Through the Future" that discussed "recent approaches and research trends not only in anticipating human behavior from videos, but also precognition in multiple other visual applications such as medical imaging, healthcare, human face aging prediction, early event prediction, autonomous driving, forecasting, etc."
During this workshop, Ph.D. candidate Pha Nguyen presented a talk on a paper co-authored with Luu entitled Multi-Camera Multiple 3D Object Tracking on the Move for Autonomous Vehicles, also co-authored by computer science and computer engineering students Pha Nguyen, Kha Gia Quach, Chi Nhan Duong, Ngan Le and Xuan-Bac Nguyen. Other students who co-authored works presented their research in the conference, as well, such as DirecFormer: A Directed Attention in Transformer Approach to Robust Action Recognition by Luu, Thanh-Dat Truong, Quoc-Huy Bui, Chi Nhan Duong, Son Lam Phung, Xin Li and Han-Seok Seo, an associate professor in food science.
In addition to presenting premier-quality research, the students joined the CVPR Mentoring Sessions hosted by experienced and leading artificial intelligence researchers. The team attended several workshops, short courses and networked with top sponsors like Amazon Science, Google, Meta, Microsoft, Tesla, Sony, TikTok and more. Additional information about this conference can be found on the CVPR 2022 website or on the CVIU Lab website.
Contacts
Dani Jackson, media specialist
Computer Science and Computer Engineering
417-209-7865,
dj016@uark.edu
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