15 citations · 30 across the 7 of their papers we have counts for
5 papers · 2 filters
Locate n' Rotate: Two-stage Openable Part Detection with Foundation Model Priors
Siqi Li, Xiaoxue Chen, Haoyu Cheng +3
Detecting the openable parts of articulated objects is crucial for downstream applications in intelligent robotics, such as pulling a drawer. This task poses a multitasking challen…
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…
Learning Feature Inversion for Multi-class Anomaly Detection under General-purpose COCO-AD Benchmark
Jiangning Zhang, Chengjie Wang, Xiangtai Li +5
Anomaly detection (AD) is often focused on detecting anomaly areas for industrial quality inspection and medical lesion examination. However, due to the specific scenario targets,…
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…
Dual-path Frequency Discriminators for Few-shot Anomaly Detection
Yuhu Bai, Jiangning Zhang, Zhaofeng Chen +3
Few-shot anomaly detection (FSAD) plays a crucial role in industrial manufacturing. However, existing FSAD methods encounter difficulties leveraging a limited number of normal samp…