3 accepted papers
In industrial point cloud analysis, detecting subtle anomalies demands high-resolution spatial data, yet prevailing benchmarks emphasize low-resolution inputs. To address this disparity, we propose a scalable pipeline for generating realistic and subtle 3D anomalies. Employing this pipeline, we deve
Anomaly detection (AD) is essential for industrial inspection, yet existing methods typically rely on "comparing" test images to normal references from a training set. However, variations in appearance and positioning often complicate the alignment of these references with the test image, limiting d…
"Zero-shot anomaly detection (ZSAD) targets the identification of anomalies within images from arbitrary novel categories. This study introduces AdaCLIP for the ZSAD task, leveraging a pre-trained vision-language model (VLM), CLIP. AdaCLIP incorporates learnable prompts into CLIP and optimizes them…