322 citations · 388 across the 8 of their papers we have counts for
10 papers
Rethinking Auxiliary Modalities in Multimodal Zero-shot Anomaly Detection: From Semantic Fusion to Conditional Modulation
Peng Wu, Xin Ge, Yujia Sun +1
Recent foundation model-based methods have endowed RGB images with strong zero-shot anomaly detection (ZSAD) through vision-language pretraining. However, RGB observations alone re…
CoInS-Net: A Continuous Position-Aware Network for Joint Medical Image Interpolation and Segmentation
Yujia Sun, Ningfeng Que, Peiting Shi +4
Accurate medical image interpolation and anatomical structure segmentation are fundamental for computer-aided diagnosis and treatment planning. Anisotropic medical volumes with spa…
Towards Video Anomaly Detection from Event Streams: A Baseline and Benchmark Datasets
Peng Wu, Yuting Yan, Guansong Pang +4
Event-based vision, characterized by low redundancy, focus on dynamic motion, and inherent privacy-preserving properties, naturally fits the demands of video anomaly detection (VAD…
AVadCLIP: Audio-Visual Collaboration for Robust Video Anomaly Detection
Peng Wu, Wanshun Su, Guansong Pang +4
With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-based detection approaches often struggle with information insuffic…
Open-Vocabulary Video Anomaly Detection
Peng Wu, Xuerong Zhou, Guansong Pang +4
Video anomaly detection (VAD) with weak supervision has achieved remarkable performance in utilizing video-level labels to discriminate whether a video frame is normal or abnormal.…
Camouflaged Object Detection via Context-aware Cross-level Fusion
Geng Chen, Si-Jie Liu, Yu-Jia Sun +3
Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes. Accurate COD suffers from a number of challenges associated with low boun…
Boundary-Guided Camouflaged Object Detection
Yujia Sun, Shuo Wang, Chenglizhao Chen +1
Camouflaged object detection (COD), segmenting objects that are elegantly blended into their surroundings, is a valuable yet challenging task. Existing deep-learning methods often…
Context-aware Cross-level Fusion Network for Camouflaged Object Detection
Yujia Sun, Geng Chen, Tao Zhou +2
Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings. In addition, the appearance of camouflaged object…
Learning Synergistic Attention for Light Field Salient Object Detection
Yi Zhang, Geng Chen, Qian Chen +5
We propose a novel Synergistic Attention Network (SA-Net) to address the light field salient object detection by establishing a synergistic effect between multi-modal features with…
Not only Look, but also Listen: Learning Multimodal Violence Detection under Weak Supervision
Peng Wu, Jing Liu, Yujia Shi +4
Violence detection has been studied in computer vision for years. However, previous work are either superficial, e.g., classification of short-clips, and the single scenario, or un…