https://github.com/QIU023/SATS_Continual_Semantic_Seg
공식 코드SATS: Self-Attention Transfer for Continual Semantic Segmentation
Papers with Code 아카이브
Class-Incremental Semantic Segmentation
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Semantic segmentation with continous increments of classes.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YanFangCS/IPSeg
공식 코드IPSeg: Image Posterior Mitigates Semantic Drift in Class-Incremental Segmentation
https://github.com/arthurdouillard/CVPR2021_PLOP
공식 코드PLOP: Learning without Forgetting for Continual Semantic Segmentation
https://github.com/chasonjiang/fscilss
공식 코드Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation
https://github.com/clovaai/SSUL
공식 코드SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning
https://github.com/dfki-av/awt-for-ciss
공식 코드https://github.com/jihwankwak/ciss_partitioned
공식 코드Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
https://github.com/jinchaogjc/cit
공식 코드CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent Transformation
https://github.com/mmasana/FACIL
공식 코드Causes of Catastrophic Forgetting in Class-Incremental Semantic Segmentation
https://github.com/qwrawq/segacil
공식 코드SegACIL: Solving the Stability-Plasticity Dilemma in Class-Incremental Semantic Segmentation
https://github.com/roadonep/eccv2024_mbs
공식 코드Mitigating Background Shift in Class-Incremental Semantic Segmentation
https://github.com/zhangchbin/rcil
공식 코드Representation Compensation Networks for Continual Semantic Segmentation
https://github.com/zhengyuan-xie/eccv24_nest
공식 코드Early Preparation Pays Off: New Classifier Pre-tuning for Class Incremental Semantic Segmentation
https://github.com/zhihelu/ending_iss
공식 코드Evolving Knowledge Mining for Class Incremental Segmentation
https://github.com/zhu-gl-ux/adapter
공식 코드Adaptive Prototype Replay for Class Incremental Semantic Segmentation
https://github.com/zkzhang98/coinseg
공식 코드CoinSeg: Contrast Inter- and Intra- Class Representations for Incremental Segmentation
https://github.com/zkzhang98/microseg
공식 코드Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation
https://github.com/ContinualAI/avalanche
https://github.com/GMvandeVen/continual-learning
https://github.com/LTTM/IL-SemSegm
https://github.com/MECLabTUDA/ACS
https://github.com/aimagelab/mammoth
https://github.com/cvlab-yonsei/dkd
Decomposed Knowledge Distillation for Class-Incremental Semantic Segmentation
https://github.com/fcdl94/MiB
Modeling the Background for Incremental Learning in Semantic Segmentation
https://github.com/g-u-n/pycil
https://github.com/geox-lab/cmn
https://github.com/ivclab/cvs
https://github.com/kibok90/iccv2019-inc
https://github.com/mostafaelaraby/bacs-continual-semantic-segmentation
PLOP: Learning without Forgetting for Continual Semantic Segmentation
https://github.com/ngailapdi/LWF
https://github.com/panagiotamoraiti/continual-learning-challenge-2024
https://github.com/wannabeOG/ExpertNet-Pytorch
https://github.com/yaoyao-liu/mnemonics
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.