The pursuit of beauty: Converting image labels to meaningful vectors (original) (raw)

Towards Semantic Communications: Deep Learning-Based Image Semantic Coding

Qiyuan Du

2022

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An Image is Worth More Than a Thousand Words: Towards Disentanglement in the Wild

Niv Cohen

arXiv (Cornell University), 2021

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Structured Disentangled Representations

Sarthak Jain

2019

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Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation

Milton Llera

arXiv (Cornell University), 2022

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Geometry of Deep Generative Models for Disentangled Representations

SANDEEP ANAND

2018

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Image Generation and Translation with Disentangled Representations

Stefan Wermter

2018 International Joint Conference on Neural Networks (IJCNN), 2018

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DisCont: Self-Supervised Visual Attribute Disentanglement Using Context Vectors

SANDEEP ANAND

Computer Vision – ECCV 2020 Workshops, 2020

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Learning joint latent representations based on information maximization

Adrian Bors

Information Sciences, 2021

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Disentangled Dynamic Representations from Unordered Data

Romann Weber

ArXiv, 2018

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Disentangling Visual Embeddings for Attributes and Objects

Khoi Pham

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

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Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling

Yamini Bansal

Cornell University - arXiv, 2021

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PixelVAE: A Latent Variable Model for Natural Images

Aaron Courville

Cornell University - arXiv, 2016

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Disentangled Representation Learning and Generation With Manifold Optimization

Arun kumar pandey

Neural Computation

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Mask-Guided Discovery of Semantic Manifolds in Generative Models

David Rokeby

ArXiv, 2021

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Adversarial Disentanglement Using Latent Classifier for Pose-Independent Representation

Manolya Kavakli-Thorne

2019

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Extracting Visual Patterns from Deep Learning Representations

Ulises Cortés

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SCAN: Learning Abstract Hierarchical Compositional Visual Concepts

arka pal

ArXiv, 2017

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Learning Disentangled Representations of Video with Missing Data

chi zhang

ArXiv, 2020

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Constructing Visual Models with a Latent Space Approach

Jean-marc Odobez

Lecture Notes in Computer Science, 2006

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Object-Contrastive Networks: Unsupervised Object Representations

Corey Lynch

2018

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Toward a Visual Concept Vocabulary for GAN Latent Space

Sarah Schwettmann

2021

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Interpreting Deep Visual Representations via Network Dissection

David Bau

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018

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Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning

SANDEEP ANAND

arXiv (Cornell University), 2019

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SCGAN: Disentangled Representation Learning by Adding Similarity Constraint on Generative Adversarial Nets

Liangbo Chen

IEEE Access

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DRIT++: Diverse Image-to-Image Translation via Disentangled Representations

Ming-Hsuan Yang

International Journal of Computer Vision, 2020

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Learning Disentangled Expression Representations from Facial Images

Marah Halawa

arXiv (Cornell University), 2020

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Learning Conceptual Spaces with Disentangled Facets

Rana عبدالهادي عبدالسلام الشيخ

Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)

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An Evaluation of Disentangled Representation Learning for Texts

Graeme Hirst

2021

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Unsupervised Discovery of Object Landmarks as Structural Representations

Yixin Jin

2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018

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Deconvolutional Networks

ss guo

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Video understanding through the disentanglement of appearance and motion

Victor Espinoza Campos

2018

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Beyond visual semantics: Exploring the role of scene text in image understanding

Suman kumar Ghosh

Pattern Recognition Letters

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Linear Disentangled Representations and Unsupervised Action Estimation

Adam Prugel-Bennett

arXiv (Cornell University), 2020

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Evaluating the Disentanglement of Deep Generative Models through Manifold Topology

Fred Lu

ArXiv, 2021

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