anguyen8

Deep-Learning-Papers-Reading-Roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

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

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

face-vit

generative-attribution-methods

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

gScoreCAM

sam

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

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

XAI-papers

anguyen8/XAI-papers

anguyen8/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

anguyen8/gScoreCAM

anguyen8/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

anguyen8/sam

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

anguyen8/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

anguyen8/generative-attribution-methods

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

anguyen8/face-vit

anguyen8/Deep-Learning-Papers-Reading-Roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

anguyen8/peeb

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

anguyen8/deep-visualization-toolbox

Added support for Touchscreen (Ubuntu 14)

anguyen8/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

anguyen8/caffe_lrcn

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

anguyen8/chm-corr-interactive

anguyen8/biggan-am

BigGAN-AM improves the sample diversity of BigGAN and synthesizes Places365 images.

anguyen8/cnn-vis

Use CNNs to generate images

anguyen8/DCGAN-tensorflow

A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

anguyen8/shape-bias

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

anguyen8/adv_robust_autoencoder

Code for "Inverting Adversarially Robust Networks for Image Synthesis" (ACCV 2022)

anguyen8/cifar.torch

92.45% on CIFAR-10 in Torch

anguyen8/CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

anguyen8/deep-goggle

Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015

anguyen8/deepdream

anguyen8/GitResultsManager

A simple snapshotting system for managing research results using Git.

anguyen8/matplotlib_for_papers

Handout for the tutorial "Creating publication-quality figures with matplotlib"

anguyen8/opencv_contrib

Repository for OpenCV's extra modules

anguyen8/out-of-order

anguyen8/strike-with-a-pose

A simple GUI application for generating adversarial poses of an object.

anguyen8/torch-gan

anguyen8/Transformer-MM-Explainability

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.