Browse > Methodology > Representation Learning > Unsupervised Representation Learning

Unsupervised Representation Learning

41 papers with code · Methodology

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Latest papers with code

Robust Training of Vector Quantized Bottleneck Models

18 May 2020distsup/DistSup

We show that the codebook learning can suffer from poor initialization and non-stationarity of clustered encoder outputs.

LATENT VARIABLE MODELS UNSUPERVISED REPRESENTATION LEARNING VOICE CONVERSION

7
18 May 2020

Plan2Vec: Unsupervised Representation Learning by Latent Plans

ICLR 2020 geyang/plan2vec

In this paper we introduce plan2vec, an unsupervised representation learning approach that is inspired by reinforcement learning.

MOTION PLANNING UNSUPERVISED REPRESENTATION LEARNING

21
07 May 2020

Decoupling Global and Local Representations from/for Image Generation

12 Apr 2020XuezheMax/wolf

In this work, we propose a new generative model that is capable of automatically decoupling global and local representations of images in an entirely unsupervised setting.

DENSITY ESTIMATION IMAGE GENERATION STYLE TRANSFER UNSUPERVISED REPRESENTATION LEARNING

27
12 Apr 2020

Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

7 Apr 2020StefanDenn3r/Unsupervised_Anomaly_Detection_Brain_MRI

Deep unsupervised representation learning has recently led to new approaches in the field of Unsupervised Anomaly Detection (UAD) in brain MRI.

UNSUPERVISED ANOMALY DETECTION UNSUPERVISED REPRESENTATION LEARNING

8
07 Apr 2020

Label-Efficient Learning on Point Clouds using Approximate Convex Decompositions

30 Mar 2020matheusgadelha/PointCloudLearningACD

In this work, we investigate the use of Approximate Convex Decompositions (ACD) as a self-supervisory signal for label-efficient learning of point cloud representations.

UNSUPERVISED REPRESENTATION LEARNING

8
30 Mar 2020

DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation Learning

30 Mar 2020jspenmar/DeFeat-Net

In the current monocular depth research, the dominant approach is to employ unsupervised training on large datasets, driven by warped photometric consistency.

MONOCULAR DEPTH ESTIMATION UNSUPERVISED REPRESENTATION LEARNING

0
30 Mar 2020

Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds

29 Mar 2020raoyongming/PointGLR

Based on this hypothesis, we propose to learn point cloud representation by bidirectional reasoning between the local structures at different abstraction hierarchies and the global shape without human supervision.

3D OBJECT CLASSIFICATION OBJECT CLASSIFICATION UNSUPERVISED REPRESENTATION LEARNING

35
29 Mar 2020

Temporally Coherent Embeddings for Self-Supervised Video Representation Learning

21 Mar 2020csiro-robotics/TCE

We evaluate our self-supervised trained TCE model by adding a classification layer and finetuning the learned representation on the downstream task of video action recognition on the UCF101 dataset.

METRIC LEARNING SELF-SUPERVISED ACTION RECOGNITION SELF-SUPERVISED LEARNING UNSUPERVISED REPRESENTATION LEARNING

11
21 Mar 2020

Watching the World Go By: Representation Learning from Unlabeled Videos

18 Mar 2020danielgordon10/vince

Recent single image unsupervised representation learning techniques show remarkable success on a variety of tasks.

DATA AUGMENTATION UNSUPERVISED REPRESENTATION LEARNING

18
18 Mar 2020

Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning

20 Feb 2020salesforce/NeuralBayes

Disjoint Manifold Labeling: Neural Bayes allows us to formulate an objective which can optimally label samples from disjoint manifolds present in the support of a continuous distribution.

UNSUPERVISED REPRESENTATION LEARNING

21
20 Feb 2020