23 citations · 62 across the 9 of their papers we have counts for
9 papers
AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation
Khoa Vo, Sang Truong, Kashu Yamazaki +3
Temporal action proposal generation (TAPG) is a challenging task, which requires localizing action intervals in an untrimmed video. Intuitively, we as humans, perceive an action th…
Meta-Learning of NAS for Few-shot Learning in Medical Image Applications
Viet-Khoa Vo-Ho, Kashu Yamazaki, Hieu Hoang +2
Deep learning methods have been successful in solving tasks in machine learning and have made breakthroughs in many sectors owing to their ability to automatically extract features…
ABN: Agent-Aware Boundary Networks for Temporal Action Proposal Generation
Khoa Vo, Kashu Yamazaki, Sang Truong +3
Temporal action proposal generation (TAPG) aims to estimate temporal intervals of actions in untrimmed videos, which is a challenging yet plays an important role in many tasks of v…
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
Khoa Vo, Hyekang Joo, Kashu Yamazaki +4
Humans typically perceive the establishment of an action in a video through the interaction between an actor and the surrounding environment. An action only starts when the main ac…
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey
Ngan Le, Vidhiwar Singh Rathour, Kashu Yamazaki +2
Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works have demonstrated the remar…
Roughness Index and Roughness Distance for Benchmarking Medical Segmentation
Vidhiwar Singh Rathour, Kashu Yamakazi, T. Hoang Ngan Le
Medical image segmentation is one of the most challenging tasks in medical image analysis and has been widely developed for many clinical applications. Most of the existing metrics…