Actor-Action Video Classification CSC 249/449 Spring 2020 Challenge Report
Jing Shi, Zhiheng Li, Haitian Zheng, Yihang Xu, Tianyou Xiao, Weitao, Tan, Xiaoning Guo, Sizhe Li, Bin Yang, Zhexin Xu, Ruitao Lin, Zhongkai, Shangguan, Yue Zhao, Jingwen Wang, Rohan Sharma, Surya Iyer, Ajinkya, Deshmukh, Raunak Mahalik, Srishti Singh, Jayant G Rohra
TL;DR
This report summarizes the submissions and outcomes of a student-led actor-action video classification challenge conducted as a final project in a university machine vision course, highlighting various approaches and results.
Contribution
It compiles and analyzes different student submissions for the actor-action video classification challenge, providing insights into current methods and performance.
Findings
Diverse approaches were applied to actor-action classification.
Performance varied significantly across submissions.
The challenge highlighted key challenges and future directions in video classification.
Abstract
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020) at University of Rochester
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Taxonomy
TopicsHuman Pose and Action Recognition · Advanced Neural Network Applications · Advanced Vision and Imaging