Official code for paper "OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning"
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Updated
Jun 19, 2024 - Python
Official code for paper "OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning"
✌[ICLR 2024] Class Incremental Learning via Likelihood Ratio Based Task Prediction
ICLR2024 paper on Continual Learning
Official code for "Weighted Ensemble Models Are Strong Continual Learners"
Official Implementation of CVPR 2022 workshop paper "CNLL: A Semi-supervised Approach for Continual Noisy Label Learning"
The code repository for "Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks" (TPAMI 2023) in PyTorch.
The code repository for "Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need" in PyTorch.
Forward Compatible Few-Shot Class-Incremental Learning (CVPR'22)
Official implementation for CIGN
[ICLR 2023] The official code for our ICLR 2023 (top25%) paper: "Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning"
The official code for our paper "Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants".
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).
Code for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification
The code repository for "Deep Class-Incremental Learning: A Survey" in PyTorch.
The code repository for "A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning" (ICLR'23) in PyTorch
Official Implementation of the paper "Exemplar-free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation"
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).
PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)
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
The official implementation for ECCV22 paper: "FOSTER: Feature Boosting and Compression for Class-Incremental Learning" in PyTorch.
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