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DualContrast: Unsupervised Disentangling of Content and Transformations with Implicit Parameterization

27 May 2024

Papers citing "DualContrast: Unsupervised Disentangling of Content and Transformations with Implicit Parameterization"

33 / 33 papers shown

Title
StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Models Zhizhong Wang Lei Zhao Wei Xing DiffM 74 136 0 15 Aug 2023
Simple Disentanglement of Style and Content in Visual Representations Lilian Ngweta Subha Maity Alex Gittens Yuekai Sun Mikhail Yurochkin CoGe DRL 76 8 0 20 Feb 2023
Amortized Inference for Heterogeneous Reconstruction in Cryo-EM Axel Levy Gordon Wetzstein Julien N. P. Martel Frédéric Poitevin Ellen D. Zhong 60 39 0 13 Oct 2022
A Contrastive Objective for Learning Disentangled Representations Jonathan Kahana Yedid Hoshen SSL 51 13 0 21 Mar 2022
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images Axel Levy Frédéric Poitevin Julien N. P. Martel Y. Nashed A. Peck Nina Miolane Daniel Ratner Mike Dunne Gordon Wetzstein 57 43 0 15 Mar 2022
Learning Disentangled Representations in the Imaging Domain Xiao Liu Pedro Sanchez Spyridon Thermos Alison Q. OÑeil Sotirios A. Tsaftaris OOD DRL 102 72 0 26 Aug 2021
ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators Qi-Xing Huang Xiangru Huang Bo Sun Zaiwei Zhang Junfeng Jiang Minh Nguyen 81 36 0 21 Aug 2021
Learning Debiased Representation via Disentangled Feature Augmentation Jungsoo Lee Eungyeup Kim Juyoung Lee Jihyeon Janel Lee Jaegul Choo CML 69 157 0 03 Jul 2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen Yash Sharma Luigi Gresele Wieland Brendel Bernhard Schölkopf M. Besserve Francesco Locatello 104 317 0 08 Jun 2021
Unsupervised Part Segmentation through Disentangling Appearance and Shape Shilong Liu Lei Zhang Xiaohu Yang Hang Su Jun Zhu OCL 43 36 0 26 May 2021
NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Rodríguez Palafox Aljavz Bovzivc Justus Thies Matthias Nießner Angela Dai 3DH 102 108 0 01 Apr 2021
Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation Gihyun Kwon Jong Chul Ye 103 52 0 30 Mar 2021
Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement Xuanchi Ren Tao Yang Yuwang Wang Wenjun Zeng CoGe DRL 65 8 0 21 Feb 2021
Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View Xuanchi Ren Tao Yang Yuwang Wang W. Zeng CoGe OCL DRL 74 40 0 21 Feb 2021
Unsupervised Shape and Pose Disentanglement for 3D Meshes Keyang Zhou Bharat Lal Bhatnagar Gerard Pons-Moll 3DH DRL 44 78 0 22 Jul 2020
LIMP: Learning Latent Shape Representations with Metric Preservation Priors Luca Cosmo Antonio Norelli Oshri Halimi Ron Kimmel Emanuele Rodolà 67 73 0 27 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 390 18,897 0 13 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning Kaiming He Haoqi Fan Yuxin Wu Saining Xie Ross B. Girshick SSL 216 12,136 0 13 Nov 2019
Explicitly disentangling image content from translation and rotation with spatial-VAE Tristan Bepler Ellen D. Zhong Kotaro Kelley E. Brignole Bonnie Berger CoGe DRL 67 74 0 25 Sep 2019
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement Minyoung Kim Yuting Wang Pritish Sahu Vladimir Pavlovic CoGe BDL CML DRL 57 26 0 06 Sep 2019
Geometric Disentanglement for Generative Latent Shape Models Tristan Aumentado-Armstrong Stavros Tsogkas Allan D. Jepson Sven J. Dickinson DRL 56 56 0 18 Aug 2019
Explicit Disentanglement of Appearance and Perspective in Generative Models N. Detlefsen Søren Hauberg CoGe DRL 55 49 0 11 Jun 2019
On the Continuity of Rotation Representations in Neural Networks Yi Zhou Connelly Barnes Jingwan Lu Jimei Yang Hao Li 3DH 80 1,294 0 17 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 139 1,473 0 29 Nov 2018
Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders A. Jha Saket Anand Maneesh Kumar Singh V. Veeravasarapu CoGe DRL 63 128 0 27 Apr 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 68 1,356 0 16 Feb 2018
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations Abhishek Kumar P. Sattigeri Avinash Balakrishnan BDL DRL 90 523 0 02 Nov 2017
Variational Autoencoders for Deforming 3D Mesh Models Qingyang Tan Lin Gao Yu-kun Lai Shi-hong Xia AI4CE 73 201 0 13 Sep 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 434 1,824 0 25 Nov 2016
Disentangling factors of variation in deep representations using adversarial training Michaël Mathieu Jiaqi Zhao Pablo Sprechmann Aditya A. Ramesh Yann LeCun DRL CML 122 490 0 10 Nov 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 161 4,238 0 12 Jun 2016
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 316 7,396 0 05 Jun 2015
Learning Descriptors for Object Recognition and 3D Pose Estimation Paul Wohlhart Vincent Lepetit 57 449 0 20 Feb 2015