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Class Incremental Learning

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하위 태스크: 3
평가표: 6
보존된 평가 기록: 14

Incremental learning of a sequence of tasks when the task-ID is not available at test time.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ZHUANGHP/Analytic-continual-learning

공식 코드

ACIL: Analytic Class-Incremental Learning with Absolute Memorization and Privacy Protection

https://github.com/adekhovich/continual_prune_and_select

공식 코드

Continual Prune-and-Select: Class-incremental learning with specialized subnetworks

https://github.com/adityashahane10/gotham--graph-based-class-incremental-learning-framework-under-weak-supervision

공식 코드

GOTHAM: Graph Class Incremental Learning Framework under Weak Supervision

https://github.com/ahmadisahar/accv_fcil3d

공식 코드

Foundation Model-Powered 3D Few-Shot Class Incremental Learning via Training-free Adaptor

https://github.com/aignlai/gddsg

공식 코드

Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping

https://github.com/aimagelab/mammoth

공식 코드

Dark Experience for General Continual Learning: a Strong, Simple Baseline

https://github.com/albinsou/ocl_survey

공식 코드

A Comprehensive Empirical Evaluation on Online Continual Learning

https://github.com/aliayub7/CBCL

공식 코드

Cognitively-Inspired Model for Incremental Learning Using a Few Examples

https://github.com/aliayub7/cbcl-pr

공식 코드

CBCL-PR: A Cognitively Inspired Model for Class-Incremental Learning in Robotics

https://github.com/alviur/ldc

공식 코드

Exemplar-free Continual Representation Learning via Learnable Drift Compensation

https://github.com/amazon-research/sp-cil

공식 코드

Class-Incremental Learning with Strong Pre-trained Models

https://github.com/anwarmaxsum/pip

공식 코드

PIP: Prototypes-Injected Prompt for Federated Class Incremental Learning

https://github.com/arthurdouillard/CVPR2021_PLOP

공식 코드

PLOP: Learning without Forgetting for Continual Semantic Segmentation

https://github.com/arthurdouillard/dytox

공식 코드

DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion

https://github.com/arthurdouillard/incremental_learning.pytorch

공식 코드

PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning

https://github.com/arvin0313/mecoin-gfscil

공식 코드

An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning

https://github.com/ashok-arjun/CSCCT

공식 코드

Class-Incremental Learning with Cross-Space Clustering and Controlled Transfer

https://github.com/bigdata-inha/Split-and-Bridge

공식 코드

Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network

https://github.com/biomedia-mbzuai/dynammo

공식 코드

DynaMMo: Dynamic Model Merging for Efficient Class Incremental Learning for Medical Images

https://github.com/blackblitz/bcl

공식 코드

On Sequential Loss Approximation for Continual Learning

https://github.com/braincog-x/brain-cog

공식 코드

Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks

https://github.com/burakgurbuz97/sharp-continual-learning

공식 코드

SHARP: Sparsity and Hidden Activation RePlay for Neuro-Inspired Continual Learning

https://github.com/bwnzheng/lpa_icme2023

공식 코드

Preserving Locality in Vision Transformers for Class Incremental Learning

https://github.com/bwnzheng/tagfex_cvpr2025

공식 코드

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

https://github.com/byyx666/archcraft

공식 코드

Revisiting Neural Networks for Continual Learning: An Architectural Perspective

https://github.com/canpeng123/fscil_alice

공식 코드

Few-Shot Class-Incremental Learning from an Open-Set Perspective

https://github.com/chaoqi7/bsa-cil-3d

공식 코드

Boosting the Class-Incremental Learning in 3D Point Clouds via Zero-Collection-Cost Basic Shape Pre-Training

https://github.com/chaoqi7/cmip-cil

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CMIP-CIL: A Cross-Modal Benchmark for Image-Point Class Incremental Learning

https://github.com/chasonjiang/fscilss

공식 코드

Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation

https://github.com/chen-xw/drc-cil

공식 코드

Dynamic Residual Classifier for Class Incremental Learning

https://github.com/chen-yizhu/gacl

공식 코드

GACL: Exemplar-Free Generalized Analytic Continual Learning

https://github.com/chrismcclurg/fscil-acs

공식 코드

Active Class Selection for Few-Shot Class-Incremental Learning

https://github.com/clovaai/SSUL

공식 코드

SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning

https://github.com/conditionwang/fcil

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Federated Class-Incremental Learning

https://github.com/csm9493/TaskBalancedBN

공식 코드

Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning

https://github.com/czjghost/afs

공식 코드

New Insights on Relieving Task-Recency Bias for Online Class Incremental Learning

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