Fetching the paper…
Reading the bibliography…
The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects.
Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2014
Earlier work this paper cites.
Variational inference with normalizing flows
Danilo Jimenez Rezende and Shakir Mohamed · 2015
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
Earlier work this paper cites.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016
Earlier work this paper cites.
3d shape induction from 2d views of multiple objects
Matheus Gadelha, Subhransu Maji, and Rui Wang · 2017
Earlier work this paper cites.
Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge J. Belongie · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
Earlier work this paper cites.
Learning representations and generative models for 3d point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J. Guibas · 2018
Earlier work this paper cites.
Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Min-Je Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
Earlier work this paper cites.
Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 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.
Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
SDM-NET: deep generative network for structured deformable mesh
Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, and Hao Zhang · 2019
Earlier work this paper cites.
Learning single-image 3d reconstruction by generative modelling of shape, pose and shading
Paul Henderson and Vittorio Ferrari · 2019
Earlier work this paper cites.
Escaping plato’s cave: 3d shape from adversarial rendering
Philipp Henzler, Niloy J Mitra, , and Tobias Ritschel · 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.
Do deep generative models know what they don’t know?
Eric T. Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Görür, and Balaji Lakshminarayanan · 2019
Earlier work this paper cites.
Hologan: Unsupervised learning of 3d representations from natural images
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, and Yong-Liang Yang · 2019
Earlier work this paper cites.
Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge J. Belongie, and Bharath Hariharan · 2019
Earlier work this paper cites.
Disentangled image generation through structured noise injection
Yazeed Alharbi and Peter Wonka · 2020
Earlier work this paper cites.
The tools of generative art, from flash to neural networks
Jason Bailey · 2020
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
Jukebox: A generative model for music
Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, and Ilya Sutskever · 2020
Earlier work this paper cites.
Unsupervised object-centric video generation and decomposition in 3d
Paul Henderson and Christoph H. Lampert · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Towards unsupervised learning of generative models for 3d controllable image synthesis
Yiyi Liao, Katja Schwarz, Lars M. Mescheder, and Andreas Geiger · 2020
Earlier work this paper cites.
Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020
Earlier work this paper cites.
Inverse graphics gan: Learning to generate 3d shapes from unstructured 2d data
Sebastian Lunz, Yingzhen Li, Andrew W. Fitzgibbon, and Nate Kushman · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Polygen: An autoregressive generative model of 3d meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, and Peter W. Battaglia · 2020
Earlier work this paper cites.
Blockgan: Learning 3d object-aware scene representations from unlabelled images
Thu Nguyen-Phuoc, Christian Richardt, Long Mai, Yong-Liang Yang, and Niloy Mitra · 2020
Earlier work this paper cites.
Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2020
Earlier work this paper cites.
Spectral-gans for high-resolution 3d point-cloud generation
Sameera Ramasinghe, Salman H. Khan, Nick Barnes, and Stephen Gould · 2020
Earlier work this paper cites.
Graf: Generative radiance fields for 3d-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
Earlier work this paper cites.
Interpreting the latent space of gans for semantic face editing
Yujun Shen, Jinjin Gu, Xiaoou Tang, and Bolei Zhou · 2020
Cited alongside, same era.
Bringing old photos back to life
Ziyu Wan, Bo Zhang, Dongdong Chen, Pan Zhang, Dong Chen, Jing Liao, and Fang Wen · 2020
Cited alongside, same era.
Multiview neural surface reconstruction by disentangling geometry and appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, and Yaron Lipman · 2020
Cited alongside, same era.
Pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
Eric R. Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
Cited alongside, same era.
Unconstrained scene generation with locally conditioned radiance fields
Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, and Joshua M. Susskind · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
LION: latent point diffusion models for 3d shape generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis · 2022
Later among the works it cites.
Fdnerf: Few-shot dynamic neural radiance fields for face reconstruction and expression editing
Jingbo Zhang, Xiaoyu Li, Ziyu Wan, Can Wang, and Jing Liao · 2022
Later among the works it cites.
https://github.com/deep-floyd/IF , 2023
Deepfloyd · 2023
Closest in time.
Musiclm: Generating music from text
Andrea Agostinelli, Timo I. Denk, Zalán Borsos, Jesse H. Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, Matthew Sharifi, Neil Zeghidour, and Christian Havnø Frank · 2023
Closest in time.
Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation
Titas Anciukevicius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J. Mitra, and Paul Guerrero · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Cited alongside, same era.
TM-NET: deep generative networks for textured meshes
Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, and Hao (Richard) Zhang · 2021
Cited alongside, same era.
Gancraft: Unsupervised 3d neural rendering of minecraft worlds
Zekun Hao, Arun Mallya, Serge J. Belongie, and Ming-Yu Liu · 2021
Cited alongside, same era.
Octree transformer: Autoregressive 3d shape generation on hierarchically structured sequences
Moritz Ibing, Gregor Kobsik, and Leif Kobbelt · 2021
Cited alongside, same era.
Editgan: High-precision semantic image editing
Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, and Sanja Fidler · 2021
Cited alongside, same era.
Editing conditional radiance fields
Steven Liu, Xiuming Zhang, Zhoutong Zhang, Richard Zhang, Jun-Yan Zhu, and Bryan Russell · 2021
Cited alongside, same era.
Gnerf: Gan-based neural radiance field without posed camera
Quan Meng, Anpei Chen, Haimin Luo, Minye Wu, Hao Su, Lan Xu, Xuming He, and Jingyi Yu · 2021
Cited alongside, same era.
Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Xingguang Yan, Gordon Wetzstein, Leonidas J. Guibas, and Andrea Tagliasacchi · 2023
Closest in time.
Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A. Efros · 2023
Closest in time.
Objaverse-xl: A universe of 10m+ 3d objects
Matt Deitke, Ruoshi Liu, Matthew Wallingford, Huong Ngo, Oscar Michel, Aditya Kusupati, Alan Fan, Christian Laforte, Vikram Voleti, Samir Yitzhak Gadre, Eli VanderBilt, Aniruddha Kembhavi, Carl Vondrick, Georgia Gkioxari, Kiana Ehsani, Ludwig Schmidt, and Ali Farhadi · 2023
Closest in time.
Nerdi: Single-view nerf synthesis with language-guided diffusion as general image priors
Congyue Deng, Chiyu Max Jiang, Charles R. Qi, Xinchen Yan, Yin Zhou, Leonidas J. Guibas, and Dragomir Anguelov · 2023
Closest in time.
Nerfdiff: Single-image view synthesis with nerf-guided distillation from 3d-aware diffusion
Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M. Susskind, Christian Theobalt, Lingjie Liu, and Ravi Ramamoorthi · 2023
Closest in time.
threestudio: A unified framework for 3d content generation
Yuan-Chen Guo, Ying-Tian Liu, Ruizhi Shao, Christian Laforte, Vikram Voleti, Guan Luo, Chia-Hao Chen, Zi-Xin Zou, Chen Wang, Yan-Pei Cao, and Song-Hai Zhang · 2023
Closest in time.
Instruct-nerf2nerf: Editing 3d scenes with instructions
Ayaan Haque, Matthew Tancik, Alexei A. Efros, Aleksander Holynski, and Angjoo Kanazawa · 2023
Closest in time.
Aladdin: Zero-shot hallucination of stylized 3d assets from abstract scene descriptions
Ian Huang, Vrishab Krishna, Omoruyi Atekha, and Leonidas Guibas · 2023
Closest in time.
Shap-e: Generating conditional 3d implicit functions
Heewoo Jun and Alex Nichol · 2023
Closest in time.
Holofusion: Towards photo-realistic 3d generative modeling
Animesh Karnewar, Niloy J. Mitra, Andrea Vedaldi, and David Novotný · 2023
Closest in time.
3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
Closest in time.
3d-aware blending with generative nerfs
Hyunsu Kim, Gayoung Lee, Yunjey Choi, Jin-Hwa Kim, and Jun-Yan Zhu · 2023
Closest in time.
SALAD: part-level latent diffusion for 3d shape generation and manipulation
Juil Koo, Seungwoo Yoo, Minh Hieu Nguyen, and Minhyuk Sung · 2023
Closest in time.
Tada! text to animatable digital avatars
Tingting Liao, Hongwei Yi, Yuliang Xiu, Jiaxiang Tang, Yangyi Huang, Justus Thies, and Michael J. Black · 2023
Closest in time.
Magic3d: High-resolution text-to-3d content creation
Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, and Tsung-Yi Lin · 2023
Closest in time.
Realfusion 360° reconstruction of any object from a single image
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht, and Andrea Vedaldi · 2023
Closest in time.
On distillation of guided diffusion models
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2023
Closest in time.
Latent-nerf for shape-guided generation of 3d shapes and textures
Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or · 2023
Closest in time.
GPT-4 technical report
OpenAI · 2023
Closest in time.
Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin, Bing Li, Hsin-Ying Lee, Ivan Skorokhodov, Peter Wonka, Sergey Tulyakov, et al · 2023
Closest in time.
Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis
Axel Sauer, Tero Karras, Samuli Laine, Andreas Geiger, and Timo Aila · 2023
Closest in time.
GINA-3D: learning to generate implicit neural assets in the wild
Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi, Boyang Deng, Leonidas J. Guibas, Yin Zhou, and Dragomir Anguelov · 2023
Closest in time.
Learning 3d-aware image synthesis with unknown pose distribution
Zifan Shi, Yujun Shen, Yinghao Xu, Sida Peng, Yiyi Liao, Sheng Guo, Qifeng Chen, and Dit-Yan Yeung · 2023
Closest in time.
3d generation on imagenet
Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee, Peter Wonka, and Sergey Tulyakov · 2023
Closest in time.
Next3d: Generative neural texture rasterization for 3d-aware head avatars
Jingxiang Sun, Xuan Wang, Lizhen Wang, Xiaoyu Li, Yong Zhang, Hongwen Zhang, and Yebin Liu · 2023
Closest in time.
Generating part-aware editable 3d shapes without 3d supervision
Konstantinos Tertikas, Despoina Paschalidou, Boxiao Pan, Jeong Joon Park, Mikaela Angelina Uy, Ioannis Z. Emiris, Yannis Avrithis, and Leonidas J. Guibas · 2023
Closest in time.
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
Closest in time.
Learning neural duplex radiance fields for real-time view synthesis
Ziyu Wan, Christian Richardt, Aljaž Božič, Chao Li, Vijay Rengarajan, Seonghyeon Nam, Xiaoyu Xiang, Tuotuo Li, Bo Zhu, Rakesh Ranjan, et al · 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.
Magicpony: Learning articulated 3d animals in the wild
Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, and Andrea Vedaldi · 2023
Closest in time.
Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
Closest in time.
Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhizhuo Zhou and Shubham Tulsiani · 2023
Closest in time.