Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".
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Updated
Sep 11, 2020 - MATLAB
Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".
Official [WACV] Code Repository for "Saliency Guided Experience Packing for Replay in Continual Learning"
This project uses Deep Learning to extract Salient text from an image using State-of-the-Art Vision Transformer Architecture.
Deep convolutional network for saliency prediction, implemented by PyTorch
Explainability and Robustness in Metric Space
This project aims to study the kind of representations learned by ConvNets at different layers.
PVCFA: Principal Variation Context Feature Attribution - Distributed Chess for Perturbation-based Saliency Maps
Web application for 3D Visualization of Alzheimer's disease Signatures
Saliency Detection library (models, loss, utils) with PyTorch
Programming assignments to demonstrate the Applications of Data Science. These were completed as part of the Plaksha Tech Leaders Fellowship program.
implementation of Visualising Image Classification Models and Saliency Maps
Sanity checks for comparing gradient attribution maps
reference implementation of Real-time Salient Object Detection based on Division of Gaussians [Katramados/Breckon, 2011]
Code and data for the ACL 2023 NLReasoning Workshop paper "Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods" (Feldhus et al., 2023)
Neural network visualization tool after an optional model compression with parameter pruning: (integrated) gradients, guided/visual backpropagation, activation maps for the cao model on the IndianPines dataset
Visual Search Model: A Bayesian model for visual search on natural scenes.
Visualizer for PyTorch image models
The official PyTorch implementation of IEEE Transactions on Image Processing 2021 paper "Rethinking the U-shape Structure for Salient Object Detection"
Codes for the AAAI 2021 paper "Locate Globally, Segment locally: A Progressive Architecture With Knowledge Review Network for Salient Object Detection"
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