Pytorch implementation of convolutional neural network visualization techniques
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Updated
Oct 10, 2022 - Python
Pytorch implementation of convolutional neural network visualization techniques
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Code for our CVPR 2019 paper "A Simple Pooling-Based Design for Real-Time Salient Object Detection"
Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model. IEEE Transactions on Image Processing (2018)
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Official implementation of Score-CAM in PyTorch
Detect model's attention
Neural network visualization toolkit for tf.keras
Video Salient Object Detection via Fully Convolutional Networks (TIP18)
A Deep Multi-Level Network for Saliency Prediction. ICPR 2016
Unified Image and Video Saliency Modeling (ECCV 2020)
CVPR2020, Multi-scale Interactive Network for Salient Object Detection
This Toolbox contains E-measure, S-measure, weighted F & F-measure, MAE and PR curves or bar metrics for salient object detection.
RGB-D Salient Object Detection: A Survey
Revisiting Video Saliency: A Large-scale Benchmark and a New Model (CVPR18, PAMI19)
Pytorch Implementation of recent visual attribution methods for model interpretability
As part of the Explainable AI Toolkit (XAITK), XAITK-Saliency is an open source, explainable AI framework for visual saliency algorithm interfaces and implementations, built for analytics and autonomy applications.
PySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object Detection
ViNet Pushing the limits of Visual Modality for Audio Visual Saliency Prediction
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