3 citations · 6 across the 9 of their papers we have counts for
5 papers · 1 filter
Dynamic Spatio-Temporal Specialization Learning for Fine-Grained Action Recognition
Tianjiao Li, Lin Geng Foo, Qiuhong Ke +4
The goal of fine-grained action recognition is to successfully discriminate between action categories with subtle differences. To tackle this, we derive inspiration from the human…
IGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition
Yunsheng Pang, Qiuhong Ke, Hossein Rahmani +2
Human interaction recognition is very important in many applications. One crucial cue in recognizing an interaction is the interactive body parts. In this work, we propose a novel…
ERA: Expert Retrieval and Assembly for Early Action Prediction
Lin Geng Foo, Tianjiao Li, Hossein Rahmani +2
Early action prediction aims to successfully predict the class label of an action before it is completely performed. This is a challenging task because the beginning stages of diff…
Action Classification with Locality-constrained Linear Coding
Hossein Rahmani, Arif Mahmood, Du Huynh +1
We propose an action classification algorithm which uses Locality-constrained Linear Coding (LLC) to capture discriminative information of human body variations in each spatiotempo…
HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition
Hossein Rahmani, Arif Mahmood, Du Q. Huynh +1
Existing techniques for 3D action recognition are sensitive to viewpoint variations because they extract features from depth images which change significantly with viewpoint. In co…