(AAAI 2021) Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network
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Updated
Feb 3, 2021 - Python
(AAAI 2021) Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network
The code repository for "Co-Transport for Class-Incremental Learning" (ACM MM'21) in PyTorch.
Official PyTorch Implementation of PuriDivER CVPR 2022.
a PyTorch Tutorial to Class-Incremental Learning | a Distributed Training Template of CIL with core code less than 100 lines.
Official Implementation of the ECCV 2022 Paper "Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer"
Class Incremental Learning (iCaRL, EEIL, BiC) reproduce github repository.
[AAAI 2022 Oral] Static-Dynamic Co-Teaching for Class-Incremental 3D Object Detection
The official implementation for ECCV22 paper: "FOSTER: Feature Boosting and Compression for Class-Incremental Learning" in PyTorch.
Code for SCIENTIA SINICA Informationis paper "Generalized representation of local relationships for few-shot incremental learning", 局部关系泛化表征的小样本增量学习
PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)
PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).
Official Implementation of the paper "Exemplar-free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation"
The code repository for "A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning" (ICLR'23) in PyTorch
The code repository for "Deep Class-Incremental Learning: A Survey" in PyTorch.
Code for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification
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).
The official code for our paper "Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants".
[ICLR 2023] The official code for our ICLR 2023 (top25%) paper: "Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning"
Official implementation for CIGN
Forward Compatible Few-Shot Class-Incremental Learning (CVPR'22)
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