Cut and Learn for Unsupervised Object Detection and Instance S | Computer Science and Programming

Cut and Learn for Unsupervised Object Detection and Instance Segmentation

Cut-and-LEaRn (CutLER) is a simple approach for training object detection and instance segmentation models without human annotations. It outperforms previous SOTA by 2.7 times for AP50 and 2.6 times for AR on 11 benchmarks.

Paper:
https://arxiv.org/pdf/2301.11320.pdf

Github:
https://github.com/facebookresearch/CutLER

Demo:
https://colab.research.google.com/drive/1NgEyFHvOfuA2MZZnfNPWg1w5gSr3HOBb?usp=sharing

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