7 papers
MambaADv2: Evolving Duality-enhanced State Space Model for Unsupervised Anomaly Detection
Xiaobin Hu, Haoyang He, Bo Yin +5
While recent advancements in anomaly detection have demonstrated the efficacy of CNN- and Transformer-based approaches, these architectures face inherent limitations: CNNs struggle…
OpenVE-3M: A Large-Scale High-Quality Dataset for Instruction-Guided Video Editing
Haoyang He, Jie Wang, Jiangning Zhang +5
The quality and diversity of instruction-based image editing datasets are continuously increasing, yet large-scale, high-quality datasets for instruction-based video editing remain…
EfficientIML: Efficient High-Resolution Image Manipulation Localization
Jinhan Li, Haoyang He, Lei Xie +1
With imaging devices delivering ever-higher resolutions and the emerging diffusion-based forgery methods, current detectors trained only on traditional datasets (with splicing, cop…
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection
Jiangning Zhang, Haoyang He, Zhenye Gan +7
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as indust…
Learning Multi-view Anomaly Detection with Efficient Adaptive Selection
Haoyang He, Jiangning Zhang, Guanzhong Tian +2
This study explores the recently proposed and challenging multi-view Anomaly Detection (AD) task. Single-view tasks will encounter blind spots from other perspectives, resulting in…
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Haoyang He, Yuhu Bai, Jiangning Zhang +7
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers ar…