anguyen8/generative-attribution-methods

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Created about 5 years ago
Updated almost 2 years ago

anguyen8/generative-attribution-methods

anguyen8

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Code for paper [Explaining image classifiers by removing input features using generative models] [ACCV 2020] https://arxiv.org/abs/1910.04256

XAI-papers

vision-llms-are-blind

Jupyter Notebook

deepface-emd

Code for CVPR 2022 https://arxiv.org/abs/2112.04016 DeepFace-EMD Re-ranking Using Patch-wise Earth Movers Distance Improves Out-Of-Distribution Face Identification

visual-correspondence-XAI

Official code for NeurIPS 2022 paper https://arxiv.org/abs/2208.00780 Visual correspondence-based explanations improve AI robustness and human-AI team accuracy

Jupyter Notebook

sam

Code for the CVPR 2020 [ORAL] paper "SAM: The Sensitivity of Attribution Methods to Hyperparameters"

gScoreCAM

effectiveness-attribution-maps

Data for the NeurIPS 2021 paper [The effectiveness of feature attribution methods and its correlation with automatic evaluation scores] https://arxiv.org/abs/2105.14944

Jupyter Notebook

peeb

[NAACL 2024] Part-based, explainable and editable fine-grained image classifier that allows users to define a species in text

face-vit

im

Code for [ Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models? ] AACL 2022 https://arxiv.org/abs/2110.11929

caffe_lrcn

A clone from the recurrent branch of the LRCN caffe by Jeff Donahue http://jeffdonahue.com/lrcn/

chm-corr-interactive

shape-bias

Code for [The shape and simplicity biases of adversarially robust ImageNet-trained CNNs] https://arxiv.org/abs/2006.09373