Alternatives and similar repositories for Awesome_Continual-Lifelong-Incremental_learning

Users that are interested in Awesome_Continual-Lifelong-Incremental_learning are comparing it to the libraries listed below

• BIT-DA / MetaSAug
  [CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
  ☆61Updated 2 years ago
• Jingkang50 / ICCV21_SCOOD
  The Official Implementation of the ICCV-2021 Paper: Semantically Coherent Out-of-Distribution Detection.
  ☆70Updated 3 years ago
• GT-RIPL / AlwaysBeDreaming-DFCIL
  PyTorch code for the ICCV'21 paper: "Always Be Dreaming: A New Approach for Class-Incremental Learning"
  ☆64Updated 3 years ago
• silvia1993 / ROS
  Rotation-based Open Set
  ☆41Updated 2 years ago
• BIGKnight / Energy-Based-Open-World-Uncertainty-Modeling-for-Confidence-Calibration
  the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"
  ☆41Updated 4 years ago
• JoyHuYY1412 / DDE_CIL
  ☆60Updated 3 years ago
• fiveai / LAME
  This code accompanies the paper "Parameter-free Online Test-time Adaptation".
  ☆76Updated 3 years ago
• BIT-DA / DDA
  Code release for "Dynamic Domain Adaptation for Efficient Inference" (CVPR 2021)
  ☆33Updated 3 years ago
• Haoang97 / MEDI
  Source code for ICLR 2022 paper "Meta Discovery: Learning to Discover Novel Classes given Very Limited Data".
  ☆17Updated last year
• chrysts / geodesic_continual_learning
  This is a public repository for:
  ☆39Updated 4 years ago
• thuml / Transferable-Query-Selection
  Code Release for "Transferable Query Selection for Active Domain Adaptation"(CVPR2021)
  ☆25Updated 3 years ago
• sud0301 / essentials_for_CIL
  Official repository of the paper 'Essentials for Class Incremental Learning'
  ☆42Updated 4 years ago
• JosephKJ / ELI
  (CVPR 2022) Energy-based Latent Aligner for Incremental Learning
  ☆52Updated 2 years ago
• tim-learn / DINE
  code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"
  ☆82Updated last year
• siyuhuang / TOD
  PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021
  ☆41Updated 3 years ago
• lucasmansilla / DGvGS
  Domain Generalization via Gradient Surgery
  ☆50Updated 3 years ago
• Albert0147 / G-SFDA
  code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'
  ☆107Updated 3 years ago
• LeeHyuck / ABC
  pytorch implementation of ABC : Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
  ☆39Updated 11 months ago
• koncle / TSMLDG
  Generalizable Semantic Segmentation viaModel-agnostic Learning and Target-specificNormalization
  ☆28Updated 5 years ago
• ispc-lab / BMD
  [ECCV 2022] The official repository of our paper "BMD: A General Class-balanced Multicentric Dynamic Prototype Strategy for Source-free D…
  ☆34Updated 2 years ago
• DianCh / AdaContrast
  Official repository of CVPR '22 paper "Contrastive Test-Time Adaptation"
  ☆103Updated 3 years ago
• EricZsy / BalancedKnowledgeDistillation
  Code for "Balanced Knowledge Distillation for Long-tailed Learning"
  ☆28Updated 2 years ago
• amazon-science / crossnorm-selfnorm
  CrossNorm and SelfNorm for Generalization under Distribution Shifts, ICCV 2021
  ☆128Updated 4 years ago
• jmiemirza / DUA
  The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization (CVPR 2022)
  ☆56Updated 2 years ago
• muse1998 / Source-Free-Domain-Generalization
  An open-world scenario domain generalization code base
  ☆26Updated 2 years ago
• KaiyangZhou / ssdg-benchmark
  Benchmarks for semi-supervised domain generalization.
  ☆70Updated 3 years ago
• lileicv / PDEN
  ☆40Updated 4 years ago
• ygjwd12345 / TransDA
  Official pytorch implement for “Transformer-Based Source-Free Domain Adaptation”
  ☆70Updated 2 years ago
• asrafulashiq / dynamic-cdfsl
  Pytorch codes for NeurIPS 2021 paper titled "Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data".
  ☆32Updated 3 years ago
• GT-RIPL / FeatMatch
  PyTorch code for the paper: "FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning"
  ☆50Updated 4 years ago