CVPR (2020) 元学习、小样本、领域自适应、领域泛化、迁移学习论文汇总

论文速递 三井 ⋅ 于 1周前 ⋅ 496 阅读
来源:兔子小姐@知乎


本文整理了CVPR2020关于元学习、小样本、领域自适应、领域泛化以及迁移学习的论文,没有链接的是还没有放出来的论文,有遗漏或错误欢迎指正。

  • 元学习(meta-learning)
  • 小样本(few-shot learning)
  • 元学习与小样本/零样本结合
  • 领域泛化(domain generalization)
  • 迁移学习(transfer learning)


元学习(meta-learning)

Learning Meta Face Recognition in Unseen Domains

论文下载地址:https://arxiv.org/abs/2003.07733

Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation

论文下载地址:https://arxiv.org/abs/1911.07450

Scene-Adaptive Video Frame Interpolation via Meta-Learning

论文下载地址:https://arxiv.org/abs/2004.00779

Training Noise-Robust Deep Neural Networks via Meta-Learning

论文下载地址:https://openaccess.thecvf.com/content CVPR 2020/html/Wang Training Noise-Robust Deep Neural Networks via Meta-Learning CVPR 2020 paper.html

Learning to Forget for Meta-Learning

论文下载地址:https://arxiv.org/abs/1906.05895

Tracking by Instance Detection:A Meta-Learning Approach

论文下载地址:https://openaccess.thecvf.com/content CVPR 2020/papers/Wang Tracking by I

MetaIQA Deep Meta-Learning for No-Reference Image Quality Assessment

论文下载地址:https://arxiv.org/abs/2004.05508

iTAML:An Incremental Task-Agnostic Meta-learning Approach

论文下载地址:https://arxiv.org/abs/2003.11652


小样本(few-shot learning)

FSS-1000:A 1000-Class Dataset for Few-Shot Segmentation

论文下载地址:https://arxiv.org/abs/1907.12347

3FabRec:Fast Few-Shot Face Alignment by Reconstruction

论文下载地址:https://arxiv.org/abs/1911.10448

DeepEMD:Few-Shot Image Classification With Differentiable Earth Mover’s Distance and Structured Classifiers

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Zhang\_DeepEMD\_Few-Shot\_Image\_Classification\_With\_Differentiable\_Earth\_Movers\_Distance\_and\_CVPR\_2020\_paper.pdf

Few-Shot Class-Incremental Learning

论文下载地址:https://arxiv.org/abs/2004.10956

Few-Shot Pill Recognition

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Ling\_Few-Shot\_Pill\_Recognition\_CVPR\_2020\_paper.pdf

FGN:Fully Guided Network for Few-Shot Instance Segmentation

论文下载地址:https://arxiv.org/abs/2003.13954

Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Wang\_Few-Shot\_Learning\_of\_Part-Specific\_Probability\_Space\_for\_3D\_Shape\_Segmentation\_CVPR\_2020\_paper.pdf

Learning to Select Base Classes for Few-Shot Classification

论文下载地址:https://arxiv.org/abs/2004.00315

Semi-Supervised Learning for Few-Shot Image-to-Image Translation

论文下载地址:https://arxiv.org/abs/2003.13853

CRNet:Cross-Reference Networks for Few-Shot Segmentation

论文下载地址:https://arxiv.org/abs/2003.10658

Few-Shot Object Detection With Attention-RPN and Multi-Relation Detector

论文下载地址:https://arxiv.org/abs/1908.01998

Multi-Domain Learning for Accurate and Few-Shot Color Constancy

论文下载地址:http://www4.comp.polyu.edu.hk/\~cslzhang/paper/MDLCC.pdf

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions

论文下载地址:https://arxiv.org/abs/1812.03664

Adaptive Subspaces for Few-Shot Learning

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Simon\_Adaptive\_Subspaces\_for\_Few-Shot\_Learning\_CVPR\_2020\_paper.pdf

Few-Shot Video Classification via Temporal Alignment

论文下载地址:https://arxiv.org/abs/1906.11415

Boosting Few-Shot Learning With Adaptive Margin Loss

论文下载地址:https://arxiv.org/abs/2005.13826

TransMatch:A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning

论文下载地址:https://arxiv.org/abs/1912.09033

Instance Credibility Inference for Few-Shot Learning

论文下载地址:https://arxiv.org/abs/2003.11853

DPGN:Distribution Propagation Graph Network for Few-Shot Learning

论文下载地址:https://arxiv.org/abs/2003.14247

Adversarial Feature Hallucination Networks for Few-Shot Learning

论文下载地址:https://arxiv.org/abs/2003.13193

Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition

论文下载地址:https://arxiv.org/abs/2004.00705

Improved Few-Shot Visual Classification

论文下载地址:https://arxiv.org/abs/1912.03432


元学习与小样本/零样本:

Meta-Transfer Learning for Zero-Shot Super-Resolution

论文下载地址:https://arxiv.org/abs/2002.12213

Few-Shot Open-Set Recognition Using Meta-Learning

论文下载地址:https://arxiv.org/abs/2005.13713

Meta-Learning of Neural Architectures for Few-Shot Learning

论文下载地址:https://arxiv.org/abs/1911.11090

领域自适应(domain adaptation)

Domain Adaptation for Image Dehazing

论文下载地址:https://arxiv.org/abs/2005.04668

Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Baek\_Weakly-Supervised\_Domain\_Adaptation\_via\_GAN\_and\_Mesh\_Model\_for\_Estimating\_CVPR\_2020\_paper.pdf

One-Shot Domain Adaptation for Face Generation

论文下载地址:https://arxiv.org/abs/2003.12869

Model Adaptation Unsupervised Domain Adaptation Without Source Data

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Li\_Model\_Adaptation\_Unsupervised\_Domain\_Adaptation\_Without\_Source\_Data\_CVPR\_2020\_paper.pdf

Progressive Adversarial Networks for Fine-Grained Domain Adaptation

论文下载地址:http://ise.thss.tsinghua.edu.cn/\~mlong/doc/progressive-adversarial-networks-cvpr20.pdf

Action Segmentation With Joint Self-Supervised Temporal Domain Adaptation

论文下载地址:https://arxiv.org/abs/2003.02824

Stochastic Classifiers for Unsupervised Domain Adaptation

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Lu\_Stochastic\_Classifiers\_for\_Unsupervised\_Domain\_Adaptation\_CVPR\_2020\_paper.pdf

Spherical Space Domain Adaptation With Robust Pseudo-Label Loss

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Gu\_Spherical\_Space\_Domain\_Adaptation\_With\_Robust\_Pseudo-Label\_Loss\_CVPR\_2020\_paper.pdf

Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Xu\_Reliable\_Weighted\_Optimal\_Transport\_for\_Unsupervised\_Domain\_Adaptation\_CVPR\_2020\_paper.pdf

Universal Source-Free Domain Adaptation

论文下载地址:https://arxiv.org/abs/2004.04393

Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation

论文下载地址:https://arxiv.org/abs/2005.02066

Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Hu\_Unsupervised\_Domain\_Adaptation\_With\_Hierarchical\_Gradient\_Synchronization\_CVPR\_2020\_paper.pdf

Phase Consistent Ecological Domain Adaptation

论文下载地址:https://arxiv.org/abs/2004.04923

What Can Be Transferred Unsupervised Domain Adaptation for Endoscopic Lesions

论文下载地址:https://arxiv.org/abs/2004.11500

FDA:Fourier Domain Adaptation for Semantic Segmentation

论文下载地址:https://arxiv.org/abs/2004.05498

Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering

论文下载地址:https://arxiv.org/abs/2003.08607

Multi-Modal Domain Adaptation for Fine-Grained Action Recognition

论文下载地址:https://arxiv.org/abs/2001.09691

Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision

论文下载地址:https://arxiv.org/abs/2004.07703

Gradually Vanishing Bridge for Adversarial Domain Adaptation

论文下载地址:https://arxiv.org/abs/2003.13183

Open Compound Domain Adaptation

论文下载地址:https://arxiv.org/abs/1909.03403

Selective Transfer With Reinforced Transfer Network for Partial Domain Adaptation

论文下载地址:https://arxiv.org/abs/1905.10756

xMUDA:Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

论文下载地址:https://arxiv.org/abs/1911.12676

Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

论文下载地址:https://arxiv.org/abs/2003.00867

Towards Inheritable Models for Open-Set Domain Adaptation

论文下载地址:https://arxiv.org/abs/2004.04388

Disparity-Aware Domain Adaptation in Stereo Image Restoration

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Yan\_Disparity-Aware\_Domain\_Adaptation\_in\_Stereo\_Image\_Restoration\_CVPR\_2020\_paper.pdf

Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation

论文下载地址:https://arxiv.org/abs/2003.10275

Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation

论文下载地址:https://arxiv.org/abs/2006.06567

Enhanced Transport Distance for Unsupervised Domain Adaptation

论文下载地址:https://openaccess.thecvf.com/content\_CVPR\_2020/papers/Li\_Enhanced\_Transport\_Distance\_for\_Unsupervised\_Domain\_Adaptation\_CVPR\_2020\_paper.pdf

Light-weight Calibrator A Separable Component for Unsupervised Domain Adaptation

论文下载地址:https://arxiv.org/abs/1911.12796


领域泛化(domain generalization)

Single-Side Domain Generalization for Face Anti-Spoofing

论文下载地址:https://arxiv.org/abs/2004.14043

Learning to Learn Single Domain Generalization

论文下载地址:https://arxiv.org/abs/2003.13216


迁移学习(transfer learning)

Syn2Real Transfer Learning for Image Deraining Using Gaussian Processes

论文下载地址:https://arxiv.org/abs/2006.05580

Camera On-Boarding for Person Re-Identification Using Hypothesis Transfer Learning

论文下载地址:https://vcg.engr.ucr.edu/sites/g/files/rcwecm2661/files/2020-04/09517.pdf

Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation

论文下载地址:http://porikli.com/mysite/pdfs/porikli\%202020\%20-\%20Multi-mutual\%20consistency\%20induced\%20transfer\%20subspace\%20learning\%20for\%20human\%20motion\%20segmentation.pdf

LT-Net:Label Transfer by Learning Reversible Voxel-Wise Correspondence for One-Shot

论文下载地址:https://arxiv.org/abs/2003.07072

Transfer Learning From Synthetic to Real-Noise Denoising With Adaptive Instance

论文下载地址:https://arxiv.org/abs/2002.11244

Learning to Transfer Texture From Clothing Images to 3D Humans

论文下载地址:https://arxiv.org/abs/2003.02050

Neural Data Server A Large-Scale Search Engine for Transfer Learning

论文下载地址:https://arxiv.org/abs/2001.02799

Regularizing CNN Transfer Learning With Randomised Regression

论文下载地址:https://arxiv.org/abs/1908.05997


推荐阅读:
CVPR 2020论文大盘点
小样本学习(Few-shot Learning)综述
机器学习领域最全综述列表!
从因果关系来看小样本学习丨 NeurIPS 2020

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