| --- |
| license: cc-by-4.0 |
| --- |
| ## Introduction |
| This is the extended VisA dataset with the ground truth segmentations for each defect types for each image. It represents the dataset along with the paper "MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning" which is published on ICCV 2025 conference. |
|
|
| ## Dataset Structure |
| ``` |
| VisA_Extended/ |
| |-- candle/ |
| |-----|--- Data/ |
| |-----|-----|---- Anomaly_grouped/ |
| |-----|-----|------------|----- 000/ |
| |-----|-----|------------|------|---- image.jpg |
| |-----|-----|------------|------|---- masks/ |
| |-----|-----|------------|------|------|---- missing.png |
| |-----|-----|------------|----- 001/ |
| ... |
| |-----|-----|---- Normal |
| |-----|-----|-------|-----0000.JPG |
| ... |
| ``` |
| ## Citation |
| ``` |
| @article{MultiADS2025, |
| author = {Ylli Sadikaj and |
| Hongkuan Zhou and |
| Lavdim Halilaj and |
| Stefan Schmid and |
| Steffen Staab and |
| Claudia Plant}, |
| title = {MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection |
| and Segmentation in Zero-Shot Learning}, |
| journal = {CoRR}, |
| volume = {abs/2504.06740}, |
| year = {2025} |
| } |
| ``` |
