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Enhancing AI systems to perform tasks following human instructions can significantly boost productivity.
Recursively generated b-spline surfaces on arbitrary topological meshes
Edwin Catmull and James Clark · 1978
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Smooth subdivision surfaces based on triangles
Charles Loop · 1987
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A method for registration of 3-d shapes
P.J. Besl and Neil D. McKay · 1992
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Laplacian surface editing
Olga Sorkine, Daniel Cohen-Or, Yaron Lipman, Marc Alexa, Christian Rössl, and H-P Seidel · 2004
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Mean value coordinates for closed triangular meshes
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On linear variational surface deformation methods
Mario Botsch and Olga Sorkine · 2007
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Harmonic coordinates for character articulation
Pushkar Joshi, Mark Meyer, Tony DeRose, Brian Green, and Tom Sanocki · 2007
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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Learning representations and generative models for 3d point clouds
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Blender - a 3D modelling and rendering package
Blender Online Community · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
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Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, and Hao Su · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Dualsdf: Semantic shape manipulation using a two-level representation
Zekun Hao, Hadar Averbuch-Elor, Noah Snavely, and Serge Belongie · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Deepmetahandles: Learning deformation meta-handles of 3d meshes with biharmonic coordinates
Minghua Liu, Minhyuk Sung, Radomir Mech, and Hao Su · 2021
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Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
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Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Denoising diffusion implicit models
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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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ChangeIt3D: Language-assisted 3d shape edits and deformations
Panos Achlioptas, Ian Huang, Minhyuk Sung, Sergey Tulyakov, and Leonidas Guibas · 2022
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Text2live: Text-driven layered image and video editing
Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman, Yoni Kasten, and Tali Dekel · 2022
Neural shape deformation priors
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Lion: Latent point diffusion models for 3d shape generation
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Sine: Single image editing with text-to-image diffusion models
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Bridging clip and stylegan through latent alignment for image editing
Wanfeng Zheng, Qiang Li, Xiaoyan Guo, Pengfei Wan, and Zhongyuan Wang · 2022
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Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A. Efros · 2023
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Palm: Scaling language modeling with pathways
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Vqgan-clip: Open domain image generation and editing with natural language guidance
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Diffusionclip: Text-guided diffusion models for robust image manipulation
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Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2023
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Neural wavelet-domain diffusion for 3d shape generation, inversion, and manipulation
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Yao-Chih Lee, Ji-Ze Genevieve Jang, Yi-Ting Chen, Elizabeth Qiu, and Jia-Bin Huang · 2023
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3dqd: Generalized deep 3d shape prior via part-discretized diffusion process
Yuhan Li, Yishun Dou, Xuanhong Chen, Bingbing Ni, Yilin Sun, Yutian Liu, and Fuzhen Wang · 2023
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Meshdiffusion: Score-based generative 3d mesh modeling
Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, and Weiyang Liu · 2023
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X-mesh: Towards fast and accurate text-driven 3d stylization via dynamic textual guidance, 2023
Yiwei Ma, Xiaioqing Zhang, Xiaoshuai Sun, Jiayi Ji, Haowei Wang, Guannan Jiang, Weilin Zhuang, and Rongrong Ji · 2023
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Pc2: Projection-conditioned point cloud diffusion for single-image 3d reconstruction
Luke Melas-Kyriazi, Christian Rupprecht, and Andrea Vedaldi · 2023
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Difffacto controllable part-based 3d point cloud generation with cross diffusion
Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu, Ke Li, and Leonidas J Guibas · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Gecco: Geometrically-conditioned point diffusion models
Michał J Tyszkiewicz, Pascal Fua, and Eduard Trulls · 2023
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Inst-inpaint: Instructing to remove objects with diffusion models
Ahmet Burak Yildirim, Vedat Baday, Erkut Erdem, Aykut Erdem, and Aysegul Dundar · 2023
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