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(转)Awsome Domain-Adaptation

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发布于 2018/08/06 19:29
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Awsome Domain-Adaptation

2018-08-06 19:27:54

 

This blog is copied from: https://github.com/zhaoxin94/awsome-domain-adaptation 

 

This repo is a collection of AWESOME things about domian adaptation,including papers,code etc.Feel free to star and fork.

Contents

Papers

Overview

  • Deep Visual Domain Adaptation: A Survey [arXiv 2018]
  • Domain Adaptation for Visual Applications: A Comprehensive Survey [arXiv 2017]

Theory

  • Analysis of Representations for Domain Adaptation [NIPS2006]
  • A theory of learning from different domains [ML2010]
  • Learning Bounds for Domain Adaptation [NIPS2007]

Unsupervised DA

Adversarial Methods

Network Methods

  • Boosting Domain Adaptation by Discovering Latent Domains [CVPR2018]
  • Residual Parameter Transfer for Deep Domain Adaptation [CVPR2018]
  • Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation [AAAI2018]
  • Deep CORAL: Correlation Alignment for Deep Domain Adaptation [ECCV2016]
  • Deep Domain Confusion: Maximizing for Domain Invariance [Arxiv 2014]

Optimal Transport

Incremental Methods

  • Incremental Adversarial Domain Adaptation for Continually Changing Environments [ICRA2018]
  • Continuous Manifold based Adaptation for Evolving Visual Domains [CVPR2014]

Other Methods

  • Unsupervised Domain Adaptation with Distribution Matching Machines [AAAI2018]
  • Self-Ensembling for Visual Domain Adaptation [ICLR2018 Poster]
  • Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation [ICLR2018 Poster]
  • Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation [CVPR2018]
  • Associative Domain Adaptation [ICCV2017] [TensorFlow]
  • Learning Transferrable Representations for Unsupervised Domain Adaptation [NIPS2016]

Zero-shot DA

Few-shot DA

Image-to-Image Translation

Open Set DA

Partial DA

Multi source DA

  • Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift [CVPR2018]

Applications

Object Detection

  • Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation [CVPR2018]
  • Domain Adaptive Faster R-CNN for Object Detection in the Wild [CVPR2018]

Semantic Segmentation

  • Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018]
  • Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017]

Person Re-identification

  • Person Transfer GAN to Bridge Domain Gap for Person Re-Identification [CVPR2018]
  • Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification [CVPR2018]

Others

  • Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer [CVPR2018]

Benchmarks

 

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