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We present DreamBeast, a novel method based on score distillation sampling (SDS) for generating fantastical 3D animal assets composed of distinct parts.
Modeling by example
Thomas Funkhouser, Michael Kazhdan, Philip Shilane, Patrick Min, William Kiefer, Ayellet Tal, Szymon Rusinkiewicz, and David Dobkin · 2004
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A probabilistic model for component-based shape synthesis
Evangelos Kalogerakis, Siddhartha Chaudhuri, Daphne Koller, and Vladlen Koltun · 2012
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Attribit: content creation with semantic attributes
Siddhartha Chaudhuri, Evangelos Kalogerakis, Stephen Giguere, and Thomas Funkhouser · 2013
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Design and fabrication by example
Adriana Schulz, Ariel Shamir, David IW Levin, Pitchaya Sitthi-Amorn, and Wojciech Matusik · 2014
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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
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Text2shape: Generating shapes from natural language by learning joint embeddings
Kevin Chen, Christopher B Choy, Manolis Savva, Angel X Chang, Thomas Funkhouser, and Silvio Savarese · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
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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
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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3d shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
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Objaverse: A universe of annotated 3d objects
Matt Deitke, Dustin Schwenk, Jordi Salvador, Luca Weihs, Oscar Michel, Eli VanderBilt, Ludwig Schmidt, Kiana Ehsani, Aniruddha Kembhavi, and Ali Farhadi · 2022
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Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
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Dreamfusion: Text-to-3d using 2d diffusion, 2022
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2022
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Photorealistic text-to-image diffusion models with deep language understanding, 2022
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation, 2022
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, and Greg Shakhnarovich · 2022
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A simple baseline for open-vocabulary semantic segmentation with pre-trained vision-language model, 2022
Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Han Hu, and Xiang Bai · 2022
Cited alongside, same era.
Training-free layout control with cross-attention guidance
Minghao Chen, Iro Laina, and Andrea Vedaldi · 2023
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Progressive3d: Progressively local editing for text-to-3d content creation with complex semantic prompts, 2023
Xinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li, Lei Zhang, Jian Zhang, and Li Yuan · 2023
Cited alongside, same era.
Diffusion self-guidance for controllable image generation
Dave Epstein, Allan Jabri, Ben Poole, Alexei A. Efros, and Aleksander Holynski · 2023
Cited alongside, same era.
Localized text-to-image generation for free via cross attention control
Yutong He, Ruslan Salakhutdinov, J. Zico Kolter, and Mona Lisa · 2023
Generating part-aware editable 3d shapes without 3d supervision
Konstantinos Tertikas, Despoina Paschalidou, Boxiao Pan, Jeong Joon Park, Mikaela Angelina Uy, Ioannis Emiris, Yannis Avrithis, and Leonidas Guibas · 2023
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Cg3d: Compositional generation for text-to-3d via gaussian splatting
Alexander Vilesov, Pradyumna Chari, and Achuta Kadambi · 2023
Later among the works it cites.
Ov-parts: Towards open-vocabulary part segmentation
Meng Wei, Xiaoyu Yue, Wenwei Zhang, Shu Kong, Xihui Liu, and Jiangmiao Pang · 2023
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MagicPony: Learning articulated 3d animals in the wild
Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, and Andrea Vedaldi · 2023
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Gaussiandreamer: Fast generation from text to 3d gaussian splatting with point cloud priors
Taoran Yi, Jiemin Fang, Guanjun Wu, Lingxi Xie, Xiaopeng Zhang, Wenyu Liu, Qi Tian, and Xinggang Wang · 2023
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Cited alongside, same era.
Lrm: Large reconstruction model for single image to 3d
Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, and Hao Tan · 2023
Cited alongside, same era.
Dreamwaltz: Make a scene with complex 3d animatable avatars
Yukun Huang, Jianan Wang, Ailing Zeng, He Cao, Xianbiao Qi, Yukai Shi, Zheng-Jun Zha, and Lei Zhang · 2023
Cited alongside, same era.
Farm3D: Learning articulated 3d animals by distilling 2d diffusion
Tomas Jakab, Ruining Li, Shangzhe Wu, Christian Rupprecht, and Andrea Vedaldi · 2023
Cited alongside, same era.
3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
Cited alongside, same era.
Dense text-to-image generation with attention modulation
Yunji Kim, Jiyoung Lee, Jin-Hwa Kim, Jung-Woo Ha, and Jun-Yan Zhu · 2023
Cited alongside, same era.
Magic3d: High-resolution text-to-3d content creation, 2023
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
Cited alongside, same era.
Geodream: Disentangling 2d and geometric priors for high-fidelity and consistent 3d generation
Baorui Ma, Haoge Deng, Junsheng Zhou, Yu-Shen Liu, Tiejun Huang, and Xinlong Wang · 2023
Cited alongside, same era.
Later among the works it cites.
Cat-seg: Cost aggregation for open-vocabulary semantic segmentation, 2024
Seokju Cho, Heeseong Shin, Sunghwan Hong, Anurag Arnab, Paul Hongsuck Seo, and Seungryong Kim · 2024
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Disentangled 3d scene generation with layout learning, 2024
Dave Epstein, Ben Poole, Ben Mildenhall, Alexei A. Efros, and Aleksander Holynski · 2024
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Scaling rectified flow transformers for high-resolution image synthesis, 2024
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Kyle Lacey, Alex Goodwin, Yannik Marek, and Robin Rombach · 2024
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Graphdreamer: Compositional 3d scene synthesis from scene graphs
Gege Gao, Weiyang Liu, Anpei Chen, Andreas Geiger, and Bernhard Schölkopf · 2024
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Vfusion3d: Learning scalable 3d generative models from video diffusion models
Junlin Han, Filippos Kokkinos, and Philip Torr · 2024
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Learning the 3d fauna of the web
Zizhang Li, Dor Litvak, Ruining Li, Yunzhi Zhang, Tomas Jakab, Christian Rupprecht, Shangzhe Wu, Andrea Vedaldi, and Jiajun Wu · 2024
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Compositional 3d scene generation using locally conditioned diffusion
Ryan Po and Gordon Wetzstein · 2024
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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, and Bernard Ghanem · 2024
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Mvdream: Multi-view diffusion for 3d generation, 2024
Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, and Xiao Yang · 2024
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Clip as rnn: Segment countless visual concepts without training endeavor
Shuyang Sun, Runjia Li, Philip Torr, Xiuye Gu, and Siyang Li · 2024
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Dreamdissector: Learning disentangled text-to-3d generation from 2d diffusion priors
Zizheng Yan, Jiapeng Zhou, Fanpeng Meng, Yushuang Wu, Lingteng Qiu, Zisheng Ye, Shuguang Cui, Guanying Chen, and Xiaoguang Han · 2024
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