16 citations · 29 across the 16 of their papers we have counts for
5 papers · 1 filter
MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection
Rui Dai, Srijan Das, Kumara Kahatapitiya +2
Action detection is an essential and challenging task, especially for densely labelled datasets of untrimmed videos. The temporal relation is complex in those datasets, including c…
SWAT: Spatial Structure Within and Among Tokens
Kumara Kahatapitiya, Michael S. Ryoo
Modeling visual data as tokens (i.e., image patches) using attention mechanisms, feed-forward networks or convolutions has been highly effective in recent years. Such methods usual…
Weakly-guided Self-supervised Pretraining for Temporal Activity Detection
Kumara Kahatapitiya, Zhou Ren, Haoxiang Li +3
Temporal Activity Detection aims to predict activity classes per frame, in contrast to video-level predictions in Activity Classification (i.e., Activity Recognition). Due to the e…
StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
Jinghuan Shang, Kumara Kahatapitiya, Xiang Li +1
Reinforcement Learning (RL) can be considered as a sequence modeling task: given a sequence of past state-action-reward experiences, an agent predicts a sequence of next actions. I…
Coarse-Fine Networks for Temporal Activity Detection in Videos
Kumara Kahatapitiya, Michael S. Ryoo
In this paper, we introduce Coarse-Fine Networks, a two-stream architecture which benefits from different abstractions of temporal resolution to learn better video representations…