billpsomas/simpool
This repo contains the official implementation of ICCV 2023 paper "Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?"
This project helps computer vision researchers and practitioners generate high-quality attention maps from their image classification models. By replacing the default pooling mechanism in convolutional networks or vision transformers, it takes an image as input and outputs a classified image alongside detailed attention maps that clearly delineate object boundaries. Anyone working with image recognition, especially those fine-tuning or interpreting deep learning models, would find this useful.
101 stars. No commits in the last 6 months.
Use this if you need to visualize exactly which parts of an image your deep learning model is focusing on to make a classification, and you require highly accurate attention maps that outline objects precisely.
Not ideal if you are looking for a pre-trained, off-the-shelf image classification solution without needing to delve into model architecture modifications or interpretability features.
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Language
Python
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Apache-2.0
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Last pushed
Dec 05, 2023
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