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Unofficial PyTorch implementation of the paper "Conditional Channel Gated Networks for Task-Aware Continual Learning"

SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping

An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

PyTorch code for ECCV 2020 paper: "Robust Re-Identification by Multiple Views Knowledge Distillation"

PyTorch code for the paper: "Perceive, Transform, and Act: Multi-Modal Attention Networks for Vision-and-Language Navigation"

PyTorch code for BMVC 2019 paper: Embodied Vision-and-Language Navigation with Dynamic Convolutional Filters

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

[TPAMI 2020] Generating Novel Views of Vehicles via Semi-parametric Guidance. A semi-parametric approach for synthesizing novel views of a rigid object from a single monocular image.

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

Keras Generative Adversarial Networks