Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
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Updated
Jun 21, 2024 - Python
Avalanche: an End-to-End Library for Continual Learning based on PyTorch.
(CVPR 2021 Oral) Open World Object Detection
PyCIL: A Python Toolbox for Class-Incremental Learning
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.
Evaluate three types of task shifting with popular continual learning algorithms.
An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning
PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
PyContinual (An Easy and Extendible Framework for Continual Learning)
A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).
A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neurocomputing).
Lifelong Learning with Dynamically Expandable Networks, ICLR 2018
A clean and simple data loading library for Continual Learning
Learning to Prompt (L2P) for Continual Learning @ CVPR22 and DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning @ ECCV22
Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling
Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.
This is the formal code implementation of the CVPR 2022 paper 'Federated Class Incremental Learning'.
CVPR 2020 Continual Learning Challenge - Submit your CL algorithm today!
The code repository for "Deep Class-Incremental Learning: A Survey" in PyTorch.
Forward Compatible Few-Shot Class-Incremental Learning (CVPR'22)
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