activity
20142024
most citedIGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition

3 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2024

Action Detection via an Image Diffusion Process

Lin Geng Foo, Tianjiao Li, Hossein Rahmani +1

Action detection aims to localize the starting and ending points of action instances in untrimmed videos, and predict the classes of those instances. In this paper, we make the obs…

cs.CV2023

A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image

Zheheng Jiang, Hossein Rahmani, Sue Black +1

Recently, deep learning based approaches have shown promising results in 3D hand reconstruction from a single RGB image. These approaches can be roughly divided into model-based ap…

cs.CR2023

GradMDM: Adversarial Attack on Dynamic Networks

Jianhong Pan, Lin Geng Foo, Qichen Zheng +4

Dynamic neural networks can greatly reduce computation redundancy without compromising accuracy by adapting their structures based on the input. In this paper, we explore the robus…

cs.CV2023

Progressive Channel-Shrinking Network

Jianhong Pan, Siyuan Yang, Lin Geng Foo +4

Currently, salience-based channel pruning makes continuous breakthroughs in network compression. In the realization, the salience mechanism is used as a metric of channel salience…

cs.CV20221 cited

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…

cs.CV20223 cited

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…