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Domain Adaptation

168 papers with code · Methodology

Domain adaptation is the task of adapting models between domains.

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Visual Representations for Semantic Target Driven Navigation

15 May 2018tensorflow/models

We propose to using high level semantic and contextual features including segmentation and detection masks obtained by off-the-shelf state-of-the-art vision as observations and use deep network to learn the navigation policy.

DOMAIN ADAPTATION VISUAL NAVIGATION

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

CVPR 2017 tensorflow/models

Collecting well-annotated image datasets to train modern machine learning algorithms is prohibitively expensive for many tasks.

UNSUPERVISED DOMAIN ADAPTATION

Domain Separation Networks

NeurIPS 2016 tensorflow/models

However, by focusing only on creating a mapping or shared representation between the two domains, they ignore the individual characteristics of each domain.

UNSUPERVISED DOMAIN ADAPTATION

Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning

25 Mar 2019jindongwang/transferlearning

In this paper, we propose a unified Transfer Channel Pruning (TCP) approach for accelerating UDA models.

TRANSFER LEARNING UNSUPERVISED DOMAIN ADAPTATION

Visual Domain Adaptation with Manifold Embedded Distribution Alignment

19 Jul 2018jindongwang/transferlearning

Existing methods either attempt to align the cross-domain distributions, or perform manifold subspace learning.

UNSUPERVISED DOMAIN ADAPTATION

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

6 Oct 2013jetpacapp/DeepBeliefSDK

We evaluate whether features extracted from the activation of a deep convolutional network trained in a fully supervised fashion on a large, fixed set of object recognition tasks can be re-purposed to novel generic tasks.

DOMAIN ADAPTATION OBJECT RECOGNITION SCENE RECOGNITION TRANSFER LEARNING

Unsupervised Cross-Domain Image Generation

7 Nov 2016kaonashi-tyc/zi2zi

We study the problem of transferring a sample in one domain to an analog sample in another domain.

DOMAIN ADAPTATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Unsupervised Image-to-Image Translation Networks

NeurIPS 2017 mingyuliutw/UNIT

Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains.

DOMAIN ADAPTATION MULTIMODAL UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION UNSUPERVISED IMAGE-TO-IMAGE TRANSLATION

Virtual to Real Reinforcement Learning for Autonomous Driving

13 Apr 2017SullyChen/Autopilot-TensorFlow

To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data.

AUTONOMOUS DRIVING DOMAIN ADAPTATION SYNTHETIC-TO-REAL TRANSLATION TRANSFER LEARNING