3 citations · 7 across the 10 of their papers we have counts for
6 papers · 1 filter
From Recognition to Prediction: Leveraging Sequence Reasoning for Action Anticipation
Xin Liu, Chao Hao, Zitong Yu +2
The action anticipation task refers to predicting what action will happen based on observed videos, which requires the model to have a strong ability to summarize the present and t…
Adversarial Robustness in RGB-Skeleton Action Recognition: Leveraging Attention Modality Reweighter
Chao Liu, Xin Liu, Zitong Yu +3
Deep neural networks (DNNs) have been applied in many computer vision tasks and achieved state-of-the-art (SOTA) performance. However, misclassification will occur when DNNs predic…
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion Model
Cong Cao, Huanjing Yue, Xin Liu +1
Diffusion-based zero-shot image restoration and enhancement models have achieved great success in various tasks of image restoration and enhancement. However, directly applying the…
Answering Diverse Questions via Text Attached with Key Audio-Visual Clues
Qilang Ye, Zitong Yu, Xin Liu
Audio-visual question answering (AVQA) requires reference to video content and auditory information, followed by correlating the question to predict the most precise answer. Althou…
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Kaishen Yuan, Zitong Yu, Xin Liu +3
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic. Existing methods suffer from overfitting iss…
A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
Chao Hao, Zitong Yu, Xin Liu +3
Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet closely-related computer vision tasks widely studied during the past decades. Though shar…