pytorch-meta-datasetA non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification
Stars: ✭ 39 (-45.83%)
simple-cnapsSource codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)
Stars: ✭ 88 (+22.22%)
SnowflakeNet(TPAMI 2022) Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer
Stars: ✭ 74 (+2.78%)
TransferlearningTransfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Stars: ✭ 8,481 (+11679.17%)
multilingual kwsFew-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus
Stars: ✭ 122 (+69.44%)
LaplacianShotLaplacian Regularized Few Shot Learning
Stars: ✭ 72 (+0%)
HiCECode for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"
Stars: ✭ 56 (-22.22%)
Meta Learning PapersMeta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Stars: ✭ 2,420 (+3261.11%)
FewCLUEFewCLUE 小样本学习测评基准,中文版
Stars: ✭ 251 (+248.61%)
MemoPainter-PyTorchAn unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.
Stars: ✭ 63 (-12.5%)
mmfewshotOpenMMLab FewShot Learning Toolbox and Benchmark
Stars: ✭ 336 (+366.67%)
MLMANACL 2019 paper:Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
Stars: ✭ 59 (-18.06%)
LLVIPLLVIP: A Visible-infrared Paired Dataset for Low-light Vision
Stars: ✭ 438 (+508.33%)
retrieval-fuse[ICCV21] Code for "RetrievalFuse: Neural 3D Scene Reconstruction with a Database"
Stars: ✭ 69 (-4.17%)
G-SFDAcode for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'
Stars: ✭ 88 (+22.22%)
FewShotDetection(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"
Stars: ✭ 188 (+161.11%)
Black-Box-TuningICML'2022: Black-Box Tuning for Language-Model-as-a-Service
Stars: ✭ 99 (+37.5%)
few-shot-gan-adaptation[CVPR '21] Official repository for Few-shot Image Generation via Cross-domain Correspondence
Stars: ✭ 198 (+175%)
sinkhorn-label-allocationSinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.
Stars: ✭ 49 (-31.94%)
ganbertEnhancing the BERT training with Semi-supervised Generative Adversarial Networks
Stars: ✭ 205 (+184.72%)
Meta-Fine-Tuning[CVPR 2020 VL3] The repository for meta fine-tuning in cross-domain few-shot learning.
Stars: ✭ 29 (-59.72%)
MeTALOfficial PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
Stars: ✭ 24 (-66.67%)
MSRGCNOfficial implementation of MSR-GCN (ICCV2021 paper)
Stars: ✭ 42 (-41.67%)
DeepCADcode for our ICCV 2021 paper "DeepCAD: A Deep Generative Network for Computer-Aided Design Models"
Stars: ✭ 74 (+2.78%)
P-tuningA novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
Stars: ✭ 593 (+723.61%)
few-shot-segmentationPyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans
Stars: ✭ 78 (+8.33%)
LearningToCompare-TensorflowTensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.
Stars: ✭ 17 (-76.39%)
C5Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Stars: ✭ 75 (+4.17%)
LibFewShotLibFewShot: A Comprehensive Library for Few-shot Learning.
Stars: ✭ 629 (+773.61%)
USOT[ICCV2021] Learning to Track Objects from Unlabeled Videos
Stars: ✭ 52 (-27.78%)
SCL📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).
Stars: ✭ 42 (-41.67%)
sib meta learnCode of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Stars: ✭ 56 (-22.22%)
WARPCode for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/
Stars: ✭ 66 (-8.33%)
flow1d[ICCV 2021 Oral] High-Resolution Optical Flow from 1D Attention and Correlation
Stars: ✭ 91 (+26.39%)
adaptAwesome Domain Adaptation Python Toolbox
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STTranSpatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Stars: ✭ 113 (+56.94%)
few-shot-lmThe source code of "Language Models are Few-shot Multilingual Learners" (MRL @ EMNLP 2021)
Stars: ✭ 32 (-55.56%)
FUSIONPyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"
Stars: ✭ 18 (-75%)
brunoa deep recurrent model for exchangeable data
Stars: ✭ 34 (-52.78%)
finetunerFinetuning any DNN for better embedding on neural search tasks
Stars: ✭ 442 (+513.89%)
CDFSL-ATA[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation
Stars: ✭ 21 (-70.83%)
InstanceRefer[ICCV 2021] InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring
Stars: ✭ 64 (-11.11%)
TRAR-VQA[ICCV 2021] TRAR: Routing the Attention Spans in Transformers for Visual Question Answering -- Official Implementation
Stars: ✭ 49 (-31.94%)
FSL-MateFSL-Mate: A collection of resources for few-shot learning (FSL).
Stars: ✭ 1,346 (+1769.44%)
PCLocPose Correction for Highly Accurate Visual Localization in Large-scale Indoor Spaces (ICCV 2021)
Stars: ✭ 37 (-48.61%)
Few-NERDCode and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"
Stars: ✭ 317 (+340.28%)
attMPTI[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation
Stars: ✭ 118 (+63.89%)