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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/ibm/constrained-fscil

공식 코드

Constrained Few-shot Class-incremental Learning

https://github.com/ifnspaml/CIL_Segmentation

공식 코드

Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels

https://github.com/ihaeyong/pfnr

공식 코드

Continual Learning: Forget-free Winning Subnetworks for Video Representations

https://github.com/ihaeyong/soft-tf

공식 코드

Soft-TransFormers for Continual Learning

https://github.com/ihaeyong/softnet-fscil

공식 코드

On the Soft-Subnetwork for Few-shot Class Incremental Learning

https://github.com/isee-laboratory/revisting_fscil

공식 코드

Rethinking Few-shot Class-incremental Learning: Learning from Yourself

https://github.com/ivsucram/cfa

공식 코드

Class-Incremental Learning via Knowledge Amalgamation

https://github.com/jaryP/Cascaded-Scaling-Classifier

공식 코드

Class incremental learning with probability dampening and cascaded gated classifier

https://github.com/jaryp/cil-margin-dampening-gated-classifier

공식 코드

Class incremental learning with probability dampening and cascaded gated classifier

https://github.com/jayatejak/gvalign

공식 코드

Robust Feature Learning and Global Variance-Driven Classifier Alignment for Long-Tail Class Incremental Learning

https://github.com/jayatejak/s3c

공식 코드

S3C: Self-Supervised Stochastic Classifiers for Few-Shot Class-Incremental Learning

https://github.com/jiahuadong/hfc

공식 코드

Heterogeneous Forgetting Compensation for Class-Incremental Learning

https://github.com/jiahuadong/lga

공식 코드

No One Left Behind: Real-World Federated Class-Incremental Learning

https://github.com/jiangpenghe/cl-lora

공식 코드

CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning

https://github.com/jianzhangcs/r-dfcil

공식 코드

R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning

https://github.com/jihwankwak/ciss_partitioned

공식 코드

Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation

https://github.com/jinchaogjc/cit

공식 코드

CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent Transformation

https://github.com/josephkj/eli

공식 코드

Energy-based Latent Aligner for Incremental Learning

https://github.com/junghunoh/closer_eccv2024

공식 코드

CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning

https://github.com/k-gyuhak/clom

공식 코드

Continual Learning Based on OOD Detection and Task Masking

https://github.com/k-gyuhak/clood

공식 코드

Learnability and Algorithm for Continual Learning

https://github.com/k-gyuhak/more

공식 코드

A Multi-Head Model for Continual Learning via Out-of-Distribution Replay

https://github.com/k-gyuhak/wptp

공식 코드

A Theoretical Study on Solving Continual Learning

https://github.com/kerrydrx/escort

공식 코드

Prompt-Based Exemplar Super-Compression and Regeneration for Class-Incremental Learning

https://github.com/khu-agi/privilege

공식 코드

Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners

https://github.com/kibok90/iccv2019-inc

공식 코드

Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild

https://github.com/kikihub/consense

공식 코드

ConSense: Continually Sensing Human Activity with WiFi via Growing and Picking

https://github.com/kitbransby/class-incremental-learning-echo

공식 코드

Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography

https://github.com/kminsoo/afc

공식 코드

Class-Incremental Learning by Knowledge Distillation with Adaptive Feature Consolidation

https://github.com/ky-ah/layup

공식 코드

Read Between the Layers: Leveraging Multi-Layer Representations for Rehearsal-Free Continual Learning with Pre-Trained Models

https://github.com/libo-huang/PrePrompt

공식 코드

PrePrompt: Predictive prompting for class incremental learning

https://github.com/lifelong-ml/shels

공식 코드

SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries

https://github.com/lilyht/cil-mgrb

공식 코드

Multi-Granularity Regularized Re-Balancing for Class Incremental Learning

https://github.com/lilyht/create

공식 코드

Reducing Class-wise Confusion for Incremental Learning with Disentangled Manifolds

https://github.com/linhaowei1/tpl

공식 코드

Class Incremental Learning via Likelihood Ratio Based Task Prediction

https://github.com/linhaowei1/tplr

공식 코드

Class Incremental Learning via Likelihood Ratio Based Task Prediction

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