[Project] Recent Class Activation Map Methods for CNNs and Vision Transformers

• pytorch-grad-cam

  5 9,483 5.0 Python

  Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

• Transformer-Explainability

  1 1,668 0.0 Jupyter Notebook

  [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

Not exactly the same but since you mentioned using ViT's attention outputs as a 2D feature map for the CAM you can consider this paper (Transformer Interpretability Beyond Attention Visualization) where they study the question of how to choose/mix the attention scores in a way that can be visualized (so similar to the CAMs). Maybe it can lead to better results. https://arxiv.org/abs/2012.09838 https://github.com/hila-chefer/Transformer-Explainability

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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