research
∙
03/26/2023
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Visual anomaly classification and segmentation are vital for automating ...
share
research
∙
03/02/2023
A Meta-Learning Approach to Predicting Performance and Data Requirements
We propose an approach to estimate the number of samples required for a ...
research
∙
09/13/2022
ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers
Annotating bounding boxes for object detection is expensive, time-consum...
research
∙
07/28/2022
SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation
Visual anomaly detection is commonly used in industrial quality inspecti...
research
∙
07/22/2022
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark
Most existing works on few-shot object detection (FSOD) focus on a setti...
research
∙
03/23/2011