30 citations · 31 across the 8 of their papers we have counts for
8 papers
MRAD: Zero-Shot Anomaly Detection with Memory-Driven Retrieval
Chaoran Xu, Chengkan Lv, Qiyu Chen +2
Zero-shot anomaly detection (ZSAD) often leverages pretrained vision or vision-language models, but many existing methods use prompt learning or complex modeling to fit the data di…
DeltaDeno: Zero-Shot Anomaly Generation via Delta-Denoising Attribution
Chaoran Xu, Chengkan Lv, Qiyu Chen +3
Anomaly generation is often framed as few-shot fine-tuning with anomalous samples, which contradicts the scarcity that motivates generation and tends to overfit category priors. We…
CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection
Qiyu Chen, Zhen Qu, Wei Luo +7
Recently, large pre-trained vision-language models have shown remarkable performance in zero-shot anomaly detection (ZSAD). With fine-tuning on a single auxiliary dataset, the mode…
Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection
Qiyu Chen, Huiyuan Luo, Haiming Yao +4
Anomaly detection plays a vital role in the inspection of industrial images. Most existing methods require separate models for each category, resulting in multiplied deployment cos…
Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection
Qiyu Chen, Huiyuan Luo, Han Gao +2
Unsupervised anomaly detection methods can identify surface defects in industrial images by leveraging only normal samples for training. Due to the risk of overfitting when learnin…
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
Qiyu Chen, Huiyuan Luo, Chengkan Lv +1
Anomaly synthesis strategies can effectively enhance unsupervised anomaly detection. However, existing strategies have limitations in the coverage and controllability of anomaly sy…
Produce Once, Utilize Twice for Anomaly Detection
Shuyuan Wang, Qi Li, Huiyuan Luo +2
Visual anomaly detection aims at classifying and locating the regions that deviate from the normal appearance. Embedding-based methods and reconstruction-based methods are two main…
The Second-place Solution for CVPR VISION 23 Challenge Track 1 -- Data Effificient Defect Detection
Xian Tao, Zhen Qu, Hengliang Luo +6
The Vision Challenge Track 1 for Data-Effificient Defect Detection requires competitors to instance segment 14 industrial inspection datasets in a data-defificient setting. This re…