Fetching the paper…
Reading the bibliography…
Leveraging multi-view diffusion models as priors for 3D optimization have alleviated the problem of 3D consistency, e.g., the Janus face problem or the content drift problem, in zero-shot text-to-3D models.
The elements of statistical learning: data mining, inference, and prediction
Trevor Hastie, Robert Tibshirani, Jerome H Friedman, and Jerome H Friedman · 2009
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
Earlier work this paper cites.
Neighbourhood consensus networks
Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2018
Earlier work this paper cites.
Leveraging 2d data to learn textured 3d mesh generation
Paul Henderson, Vagia Tsiminaki, 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.
Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
Earlier work this paper cites.
Self-calibrating neural radiance fields
Yoonwoo Jeong, Seokjun Ahn, Christopher Choy, Anima Anandkumar, Minsu Cho, and Jaesik Park · 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
Earlier work this paper cites.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Earlier work this paper cites.
Learning accurate dense correspondences and when to trust them
Prune Truong, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2021
Earlier work this paper cites.
Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
Cited alongside, same era.
Depth-supervised nerf: Fewer views and faster training for free
Kangle Deng, Andrew Liu, Jun-Yan Zhu, and Deva Ramanan · 2022
Cited alongside, same era.
Transformatcher: Match-to-match attention for semantic correspondence
Seungwook Kim, Juhong Min, and Minsu Cho · 2022
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Ref-NeRF: Structured view-dependent appearance for neural radiance fields
Debiasing scores and prompts of 2d diffusion for robust text-to-3d generation
Susung Hong, Donghoon Ahn, and Seungryong Kim · 2023
Later among the works it cites.
Dreamtime: An improved optimization strategy for text-to-3d content creation
Yukun Huang, Jianan Wang, Yukai Shi, Xianbiao Qi, Zheng-Jun Zha, and Lei Zhang · 2023
Later among the works it cites.
Holodiffusion: Training a 3d diffusion model using 2d images
Animesh Karnewar, Andrea Vedaldi, David Novotny, and Niloy J Mitra · 2023
Later among the works it cites.
Syncdreamer: Generating multiview-consistent images from a single-view image
Yuan Liu, Cheng Lin, Zijiao Zeng, Xiaoxiao Long, Lingjie Liu, Taku Komura, and Wenping Wang · 2023
Later among the works it cites.
Diffusion hyperfeatures: Searching through time and space for semantic correspondence
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T. Barron, and Pratul P. Srinivasan · 2022
Cited alongside, same era.
Genvs: Generative novel view synthesis with 3d-aware diffusion models, 2023
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
Cited alongside, same era.
Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Unsupervised semantic correspondence using stable diffusion
Eric Hedlin, Gopal Sharma, Shweta Mahajan, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, and Kwang Moo Yi · 2023
Cited alongside, same era.
Nerfacc: Efficient sampling accelerates nerfs
Ruilong Li, Hang Gao, Matthew Tancik, and Angjoo Kanazawa
Cited in the paper.
Sd4match: Learning to prompt stable diffusion model for semantic matching
Xinghui Li, Jingyi Lu, Kai Han, and Victor Prisacariu
Cited in the paper.
Grace Luo, Lisa Dunlap, Dong Huk Park, Aleksander Holynski, and Trevor Darrell · 2023
Later among the works it cites.
Mvdream: Multi-view diffusion for 3d generation
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2023
Later among the works it cites.
Viewset diffusion:(0-) image-conditioned 3d generative models from 2d data
Stanislaw Szymanowicz, Christian Rupprecht, and Andrea Vedaldi · 2023
Later among the works it cites.
Sparf: Neural radiance fields from sparse and noisy poses
Prune Truong, Marie-Julie Rakotosaona, Fabian Manhardt, and Federico Tombari · 2023
Later among the works it cites.
A tale of two features: Stable diffusion complements dino for zero-shot semantic correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani, Deqing Sun, and Ming-Hsuan Yang · 2023
Later among the works it cites.
Efficient semantic matching with hypercolumn correlation
Seungwook Kim, Juhong Min, and Minsu Cho · 2024
Closest in time.