27 citations · 47 across the 10 of their papers we have counts for
10 papers
PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer
Zhiwei Yang, Chen Gao, Mike Zheng Shou
Video anomaly detection (VAD) is a critical yet challenging task due to the complex and diverse nature of real-world scenarios. Previous methods typically rely on domain-specific t…
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
Feilong Tang, Chengzhi Liu, Zhongxing Xu +9
Recent advancements in multimodal large language models (MLLMs) have significantly improved performance in visual question answering. However, they often suffer from hallucinations…
SlowFastVAD: Video Anomaly Detection via Integrating Simple Detector and RAG-Enhanced Vision-Language Model
Zongcan Ding, Haodong Zhang, Peng Wu +4
Video anomaly detection (VAD) aims to identify unexpected events in videos and has wide applications in safety-critical domains. While semi-supervised methods trained on only norma…
AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis
Zhiwei Yang, Chen Gao, Jing Liu +3
The rapid advancements in large language models (LLMs) have spurred growing interest in LLM-based video anomaly detection (VAD). However, existing approaches predominantly focus on…
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts
Peng Wu, Xuerong Zhou, Guansong Pang +4
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-level anomalous event detection with only coarse video-level annotations available. Existing wo…
Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detection
Zhiwei Yang, Jing Liu, Peng Wu
Weakly supervised video anomaly detection (WSVAD) is a challenging task. Generating fine-grained pseudo-labels based on weak-label and then self-training a classifier is currently…
SLSG: Industrial Image Anomaly Detection by Learning Better Feature Embeddings and One-Class Classification
Minghui Yang, Jing Liu, Zhiwei Yang +1
Industrial image anomaly detection under the setting of one-class classification has significant practical value. However, most existing models struggle to extract separable featur…
Video Event Restoration Based on Keyframes for Video Anomaly Detection
Zhiwei Yang, Jing Liu, Zhaoyang Wu +2
Video anomaly detection (VAD) is a significant computer vision problem. Existing deep neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or fram…
Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection
Zhiwei Yang, Peng Wu, Jing Liu +1
Existing methods for anomaly detection based on memory-augmented autoencoder (AE) have the following drawbacks: (1) Establishing a memory bank requires additional memory space. (2)…
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…