2 citations · 5 across the 7 of their papers we have counts for
7 papers
DiffSLVA: Harnessing Diffusion Models for Sign Language Video Anonymization
Zhaoyang Xia, Carol Neidle, Dimitris N. Metaxas
Since American Sign Language (ASL) has no standard written form, Deaf signers frequently share videos in order to communicate in their native language. However, since both hands an…
Learning Causality-inspired Representation Consistency for Video Anomaly Detection
Yang Liu, Zhaoyang Xia, Mengyang Zhao +7
Video anomaly detection is an essential yet challenging task in the multimedia community, with promising applications in smart cities and secure communities. Existing methods attem…
Improving Tuning-Free Real Image Editing with Proximal Guidance
Ligong Han, Song Wen, Qi Chen +13
DDIM inversion has revealed the remarkable potential of real image editing within diffusion-based methods. However, the accuracy of DDIM reconstruction degrades as larger classifie…
Enhance Multi-Scale Spatial-Temporal Coherence for Configurable Video Anomaly Detection
Kai Cheng, Xinzhe Li, Lijuan Che
The development of unsupervised Video Anomaly Detection (VAD) relies on technologies in the field of signal processing. Since the anomaly is quite ambiguous and unbounded, differen…
SCPNet: Semantic Scene Completion on Point Cloud
Zhaoyang Xia, Youquan Liu, Xin Li +5
Training deep models for semantic scene completion (SSC) is challenging due to the sparse and incomplete input, a large quantity of objects of diverse scales as well as the inheren…
Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning
Yuxiao Chen, Long Zhao, Jianbo Yuan +5
Despite the success of fully-supervised human skeleton sequence modeling, utilizing self-supervised pre-training for skeleton sequence representation learning has been an active fi…
Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images
Qilong Zhangli, Jingru Yi, Di Liu +10
Top-down instance segmentation framework has shown its superiority in object detection compared to the bottom-up framework. While it is efficient in addressing over-segmentation, t…