Shypd.aiThe largest open index of AI toolsDenseCL is an open-source coding & development tool that implements Dense Contrastive Learning for self-supervised visual pre-training. It significantly boosts dense prediction tasks like object detection and semantic segmentation.
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DenseCL provides an open-source implementation of Dense Contrastive Learning (DenseCL) for self-supervised representation learning, which was presented at CVPR 2021. This tool is designed to benefit dense prediction tasks, including object detection and semantic segmentation, showing improvements of up to +2% AP and +3% mIoU. Its core functionality can be implemented in just 10 lines of code, making it simple to use and modify. DenseCL is flexible, decoupled from data pre-processing, and agnostic to augmentation methods, allowing for fast and adaptable training. It also introduces negligible computation overhead, being less than 1% slower than baseline methods. Pre-trained models on COCO and ImageNet are provided for convenience.
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