15 citations · 29 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 14 cited
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Jongheon Jeong, Yang Zou, Taewan Kim +3
Visual anomaly classification and segmentation are vital for automating industrial quality inspection. The focus of prior research in the field has been on training custom models f…
cs.CV2022★ 15 cited
SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation
Yang Zou, Jongheon Jeong, Latha Pemula +2
Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we present a new dataset as well as a new self-supervised learning method for ImageNet pr…