DreamLCM: Towards High-Quality Text-to-3D Generation via Latent Consistency Model

Score-Based Generative Modeling through Stochastic Differential Equations

Original

Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole. 2020b · 2011

Earlier work this paper cites.

Generative Adversarial Networks

Original

Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014

Earlier work this paper cites.

U-Net: Convolutional Networks for Biomedical Image Segmentation

Original

Olaf Ronneberger, Philipp Fischer, and Thomas Brox. 2015 · 2015

Earlier work this paper cites.

Learning Structured Output Representation using Deep Conditional Generative Models. In Advances in Neural Information Processing Systems , C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett (Eds.), Vol. 28

Kihyuk Sohn, Honglak Lee, and Xinchen Yan. 2015 · 2015

Earlier work this paper cites.

Denoising Diffusion Probabilistic Models. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. 6840–6851

Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020

Earlier work this paper cites.

Denoising Diffusion Implicit Models

Original

Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020a · 2020

Earlier work this paper cites.

Diffusion Models Beat GANs on Image Synthesis. In Advances in Neural Information Processing Systems , M. Ranzato, A. Beygelzimer, Y. Dauphin, P.S. Liang, and J. Wortman Vaughan (Eds.), Vol. 34. 8780–8794

Prafulla Dhariwal and Alexander Nichol. 2021 · 2021

Earlier work this paper cites.

Lora: Low-rank adaptation of large language models

Original

Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021

Earlier work this paper cites.

Zero-Shot Text-Guided Object Generation with Dream Fields

Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, and Ben Poole. 2021 · 2021

Earlier work this paper cites.

Gotta Go Fast When Generating Data with Score-Based Models

Original

Alexia Jolicoeur-Martineau, Ke Li, Remi Piche-Taillefer, Tal Kachman, and Ioannis Mitliagkas. 2021 · 2021

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. 2021 · 2021

Earlier work this paper cites.

Improved Denoising Diffusion Probabilistic Models. In Proceedings of the 38th International Conference on Machine Learning , Vol. 139. 8162–8171

Alexander Quinn Nichol and Prafulla Dhariwal. 2021 · 2021

Earlier work this paper cites.

Learning Transferable Visual Models From Natural Language Supervision

Original

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021

Earlier work this paper cites.

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Original

Tim Dockhorn, Arash Vahdat, and Karsten Kreis. 2022 · 2022

Earlier work this paper cites.

Classifier-Free Diffusion Guidance

Original

Jonathan Ho and Tim Salimans. 2022 · 2022

Earlier work this paper cites.

AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, and Ziwei Liu. 2022 · 2022

Earlier work this paper cites.

Auto-Encoding Variational Bayes

Original

Diederik P Kingma and Max Welling. 2022 · 2022

Earlier work this paper cites.

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Original

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2022 · 2022

Cited alongside, same era.

DreamFusion: Text-to-3D using 2D Diffusion

Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall. 2022 · 2022

Cited alongside, same era.

Hierarchical Text-Conditional Image Generation with CLIP Latents

Original

Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022

Cited alongside, same era.

High-Resolution Image Synthesis With Latent Diffusion Models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 10684–10695

Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022

Cited alongside, same era.

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. In Advances in Neural Information Processing Systems , Vol. 35. 36479–36494

Magic3D: High-Resolution Text-to-3D Content Creation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 300–309

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 · 2023

Later among the works it cites.

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Original

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2023 · 2023

Later among the works it cites.

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Original

Simian Luo, Yiqin Tan, Longbo Huang, Jian Li, and Hang Zhao. 2023 · 2023

Later among the works it cites.

Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 12663–12673

Gal Metzer, Elad Richardson, Or Patashnik, Raja Giryes, and Daniel Cohen-Or. 2023 · 2023

Later among the works it cites.