Feb. 12, 2024, 5:45 a.m. | Anupam Gupta Ashok Krishnamurthy Lisa Singh

cs.CV updates on arXiv.org arxiv.org

This paper introduces a novel segmentation framework that integrates a classifier network with a reverse HRNet architecture for efficient image segmentation. Our approach utilizes a ResNet-50 backbone, pretrained in a semi-supervised manner, to generate feature maps at various scales. These maps are then processed by a reverse HRNet, which is adapted to handle varying channel dimensions through 1x1 convolutions, to produce the final segmentation output. We strategically avoid fine-tuning the backbone network to minimize memory consumption during training. Our methodology …

architecture classifier cs.cv feature features framework fusion generate image maps network novel paper resnet resnet-50 segmentation semantic semi-supervised

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