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Found 4 papers, 3 papers with code
DocBinFormer: A Two-Level Transformer Network for Effective Document Image Binarization
Instead of using a simple vision transformer block to extract information from the image patches, the proposed architecture uses two transformer blocks for greater coverage of the extracted feature space on a global and local scale.
A Layer-Wise Tokens-to-Token Transformer Network for Improved Historical Document Image Enhancement
Instead of using a simple ViT and hard splitting of images for the document image enhancement task, we employed a progressive tokenization technique to capture this local information from an image to achieve more effective results.
Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?
In the field of medical image segmentation, polyp segmentation holds a position of high importance, thus creating a model which is robust and precise is quite challenging.
Ranked #28 on
Medical Image Segmentation
on CVC-ClinicDB
Effective Document Image Enhancement Using tokens-to-token Transformer Network
Instead of using a simple ViT and hard splitting of images for the document image enhancement task, we employed a progressive tokeniza-tion technique to capture this local information from an image for achieving more effective results.
Ranked #1 on
Binarization
on H-DIBCO 2012
