Fetching the paper…
Reading the bibliography…
Denoising diffusion models are a powerful type of generative models used to capture complex distributions of real-world signals.
Mcmc-based image reconstruction with uncertainty quantification
Johnathan M Bardsley · 2012
Earlier work this paper cites.
Plug-and-play priors for model based reconstruction
Singanallur Venkatakrishnan, Charles A. Bouman, and Brendt Wohlberg · 2013
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
Earlier work this paper cites.
Déja vu: Motion prediction in static images
Silvia L Pintea, Jan C van Gemert, and Arnold WM Smeulders · 2014
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
Earlier work this paper cites.
Dense optical flow prediction from a static image
Jacob Walker, Abhinav Gupta, and Martial Hebert · 2015
Earlier work this paper cites.
An uncertain future: Forecasting from static images using variational autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert · 2016
Earlier work this paper cites.
Generative visual manipulation on the natural image manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A. Efros · 2016
Earlier work this paper cites.
The little engine that could: Regularization by denoising (red)
Yaniv Romano, Michael Elad, and Peyman Milanfar · 2017
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
The pose knows: Video forecasting by generating pose futures
Jacob Walker, Kenneth Marino, Abhinav Gupta, and Martial Hebert · 2017
Earlier work this paper cites.
Conditional neural processes
Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Rezende, and SM Ali Eslami · 2018
Earlier work this paper cites.
Neural scene representation and rendering
SM Ali Eslami, Danilo Jimenez Rezende, Frederic Besse, Fabio Viola, Ari S Morcos, Marta Garnelo, Avraham Ruderman, Andrei A Rusu, Ivo Danihelka, Karol Gregor, et al · 2018
Earlier work this paper cites.
Stereo magnification: Learning view synthesis using multiplane images
Tinghui Zhou, Richard Tucker, John Flynn, Graham Fyffe, and Noah Snavely · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 2018
Earlier work this paper cites.
Im2flow: Motion hallucination from static images for action recognition
Ruohan Gao, Bo Xiong, and Kristen Grauman · 2018
Earlier work this paper cites.
Flow-grounded spatial-temporal video prediction from still images
Yijun Li, Chen Fang, Jimei Yang, Zhaowen Wang, Xin Lu, and Ming-Hsuan Yang · 2018
Earlier work this paper cites.
Learning category-specific mesh reconstruction from image collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A Efros, and Jitendra Malik · 2018
Earlier work this paper cites.
Attentive neural processes
Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, Ali Eslami, Dan Rosenbaum, Oriol Vinyals, and Yee Whye Teh · 2019
Earlier work this paper cites.
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
Earlier work this paper cites.
Video enhancement with task-oriented flow
Tianfan Xue, Baian Chen, Jiajun Wu, Donglai Wei, and William T Freeman · 2019
Earlier work this paper cites.
Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Earlier work this paper cites.
Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
Cited alongside, same era.
Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
Cited alongside, same era.
Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
Cited alongside, same era.
Softmax splatting for video frame interpolation
Simon Niklaus and Feng Liu · 2020
Cited alongside, same era.
Ganspace: Discovering interpretable gan controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
Cited alongside, same era.
Stylerig: Rigging stylegan for 3d control over portrait images
Restyle: A residual-based stylegan encoder via iterative refinement
Yuval Alaluf, Or Patashnik, and Daniel Cohen-Or · 2021
Later among the works it cites.
Encoding in style: a stylegan encoder for image-to-image translation
Elad Richardson, Yuval Alaluf, Or Patashnik, Yotam Nitzan, Yaniv Azar, Stav Shapiro, and Daniel Cohen-Or · 2021
Later among the works it cites.
Designing an encoder for stylegan image manipulation
Omer Tov, Yuval Alaluf, Yotam Nitzan, Or Patashnik, and Daniel Cohen-Or · 2021
Later among the works it cites.
Get3d: A generative model of high quality 3d textured shapes learned from images
Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler · 2022
Later among the works it cites.
Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
Later among the works it cites.
Solving inverse problems in medical imaging with score-based generative models
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ayush Tewari, Mohamed Elgharib, Gaurav Bharaj, Florian Bernard, Hans-Peter Seidel, Patrick Pérez, Michael Zollhofer, and Christian Theobalt · 2020
Cited alongside, same era.
Interfacegan: Interpreting the disentangled face representation learned by gans
Yujun Shen, Ceyuan Yang, Xiaoou Tang, and Bolei Zhou · 2020
Cited alongside, same era.
Image2stylegan++: How to edit the embedded images?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2020
Cited alongside, same era.
Semantic photo manipulation with a generative image prior
David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, and Antonio Torralba · 2020
Cited alongside, same era.
Collaborative learning for faster stylegan embedding
Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, and Xiaokang Yang · 2020
Cited alongside, same era.
Adversarial latent autoencoders
Stanislav Pidhorskyi, Donald A Adjeroh, and Gianfranco Doretto · 2020
Cited alongside, same era.
Pie: Portrait image embedding for semantic control
Ayush Tewari, Mohamed Elgharib, Florian Bernard, Hans-Peter Seidel, Patrick Pérez, Michael Zollhöfer, and Christian Theobalt · 2020
Cited alongside, same era.
Yang Song, Liyue Shen, Lei Xing, and Stefano Ermon · 2022
Later among the works it cites.
Generalizable patch-based neural rendering
Mohammed Suhail, Carlos Esteves, Leonid Sigal, and Ameesh Makadia · 2022
Later among the works it cites.
Guess what moves: unsupervised video and image segmentation by anticipating motion
Subhabrata Choudhury, Laurynas Karazija, Iro Laina, Andrea Vedaldi, and Christian Rupprecht · 2022
Later among the works it cites.
High-fidelity gan inversion for image attribute editing
Tengfei Wang, Yong Zhang, Yanbo Fan, Jue Wang, and Qifeng Chen · 2022
Later among the works it cites.
Diffrf: Rendering-guided 3d radiance field diffusion
Norman Müller, , Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, and Matthias Nießner · 2023
Closest in time.
Neuralfield-ldm: Scene generation with hierarchical latent diffusion models
Seung Wook Kim, Bradley Brown, Kangxue Yin, Karsten Kreis, Katja Schwarz, Daiqing Li, Robin Rombach, Antonio Torralba, and Sanja Fidler · 2023
Closest in time.
Generative novel view synthesis with 3d-aware diffusion models
Eric R Chan, Koki Nagano, Matthew A Chan, Alexander W Bergman, Jeong Joon Park, Axel Levy, Miika Aittala, Shalini De Mello, Tero Karras, and Gordon Wetzstein · 2023
Closest in time.
Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhizhuo Zhou and Shubham Tulsiani · 2023
Closest in time.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2023
Closest in time.
Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation
Titas Anciukevičius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J Mitra, and Paul Guerrero · 2023
Closest in time.
Laser: Latent set representations for 3d generative modeling
Pol Moreno, Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Rosalia G Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, and Danilo J Rezende · 2023
Closest in time.
Holodiffusion: Training a 3d diffusion model using 2d images
Animesh Karnewar, Andrea Vedaldi, David Novotny, and Niloy Mitra · 2023
Closest in time.
Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, and Jong Chul Ye · 2023
Closest in time.
Pseudoinverse-guided diffusion models for inverse problems
Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz · 2023
Closest in time.
Learning to render novel views from wide-baseline stereo pairs
Yilun Du, Cameron Smith, Ayush Tewari, and Vincent Sitzmann · 2023
Closest in time.
Novel view synthesis with diffusion models
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, and Mohammad Norouzi · 2023
Closest in time.
Consistent view synthesis with pose-guided diffusion models
Hung-Yu Tseng, Qinbo Li, Changil Kim, Suhib Alsisan, Jia-Bin Huang, and Johannes Kopf · 2023
Closest in time.
Learning controllable 3d diffusion models from single-view images
Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, and Josh Susskind · 2023
Closest in time.
Text2room: Extracting textured 3d meshes from 2d text-to-image models
Lukas Höllein, Ang Cao, Andrew Owens, Justin Johnson, and Matthias Nießner · 2023
Closest in time.
Scenescape: Text-driven consistent scene generation
Rafail Fridman, Amit Abecasis, Yoni Kasten, and Tali Dekel · 2023
Closest in time.