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Multi-View Correlation Distillation for Incremental Object Detection
[article]
2021
arXiv
pre-print
In real applications, new object classes often emerge after the detection model has been trained on a prepared dataset with fixed classes. Due to the storage burden and the privacy of old data, sometimes it is impractical to train the model from scratch with both old and new data. Fine-tuning the old model with only new data will lead to a well-known phenomenon of catastrophic forgetting, which severely degrades the performance of modern object detectors. In this paper, we propose a novel
arXiv:2107.01787v1
fatcat:o5xgcdrc6fbcngi3lcd6jq6loe