4 papers
Towards Efficient Vision State Space Models via Token Merging
Jinyoung Park, Minseok Son, Changick Kim
State Space Models (SSMs) have emerged as powerful architectures in computer vision, yet improving their computational efficiency remains crucial for practical and scalable deploym…
Difficulty-aware Balancing Margin Loss for Long-tailed Recognition
Minseok Son, Inyong Koo, Jinyoung Park +1
When trained with severely imbalanced data, deep neural networks often struggle to accurately recognize classes with only a few samples. Previous studies in long-tailed recognition…
VideoMamba: Spatio-Temporal Selective State Space Model
Jinyoung Park, Hee-Seon Kim, Kangwook Ko +2
We introduce VideoMamba, a novel adaptation of the pure Mamba architecture, specifically designed for video recognition. Unlike transformers that rely on self-attention mechanisms…
Flow-Assisted Motion Learning Network for Weakly-Supervised Group Activity Recognition
Muhammad Adi Nugroho, Sangmin Woo, Sumin Lee +4
Weakly-Supervised Group Activity Recognition (WSGAR) aims to understand the activity performed together by a group of individuals with the video-level label and without actor-level…