Fetching the paper…
Reading the bibliography…
Natural language interaction is a promising direction for democratizing 3D shape design.
ScanRefer: 3D object localization in RGB-D scans using natural language
Z. Dave Chen, Angel X. Chang, and Matthias Nießner. 2019 · 1912
Earlier work this paper cites.
Convention: A philosophical study
David Lewis. 1969 · 1969
Earlier work this paper cites.
ReferItGame: Referring to objects in photographs of natural scenes
Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, and Tamara Berg L. 2014 · 2014
Earlier work this paper cites.
InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel. 2016 · 2016
Earlier work this paper cites.
beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loïc Matthey, Arka Pal, Christopher P. Burgess, Xavier Glorot, Matthew M. Botvinick, Shakir Mohamed, and Alexander Lerchner. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Disentangling by factorising
Hyunjik Kim and Andriy Mnih. 2018 · 2018
Earlier work this paper cites.
Variational inference of disentangled latent concepts from unlabeled observations
Abhishek Kumar, Prasanna Sattigeri, and Avinash Balakrishnan. 2018 · 2018
Earlier work this paper cites.
ShapeGlot: Learning language for shape differentiation
Panos Achlioptas, Judy Fan, Robert D. Hawkins, Noah D. Goodman, and Leonidas J. Guibas. 2019 · 2019
Earlier work this paper cites.
Geometric disentanglement for generative latent shape models
Tristan Aumentado-Armstrong, Stavros Tsogkas, Allan Jepson, and Sven Dickinson. 2019 · 2019
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang. 2019 · 2019
Earlier work this paper cites.
Structured disentangled representations
Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer G. Dy, and Jan-Willem van de Meent. 2019 · 2019
Cited alongside, same era.
Auto-encoding total correlation explanation
Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, and A. G. Galstyan. 2019 · 2019
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
ReferIt3D: Neural listeners for fine-grained 3d object identification in real-world scenes
Panos Achlioptas, Ahmed Abdelreheem, Fei Xia, Mohamed Elhoseiny, and Leonidas J. Guibas. 2020 · 2020
Cited alongside, same era.
Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan. 2020 · 2020
Cited alongside, same era.
Language grounding with 3d objects
Jesse Thomason, Mohit Shridhar, Yonatan Bisk, Chris Paxton, and Luke Zettlemoyer. 2021 · 2021
Later among the works it cites.
ChangeIt3D: Language-assisted 3d shape edits and deformations
Panos Achlioptas, Ian Huang, Minhyuk Sung, Sergey Tulyakov, and Leonidas Guibas. 2022 · 2022
Closest in time.
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
Closest in time.
Zero-shot text-guided object generation with dream fields
Ajay Jain, Ben Mildenhall, Jonathan T Barron, Pieter Abbeel, and Ben Poole. 2022 · 2022
Closest in time.
Partglot: Learning shape part segmentation from language reference games
Juil Koo, Ian Huang, Panos Achlioptas, Leonidas J Guibas, and Minhyuk Sung. 2022 · 2022
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
StructEdit: Learning structural shape variations
Kaichun Mo, Paul Guerrero, Li Yi, Hao Su, Peter Wonka, Niloy J Mitra, and Leonidas J Guibas. 2020 · 2020
Cited alongside, same era.
DeformSyncNet: Deformation transfer via synchronized shape deformation spaces
Minhyuk Sung, Zhenyu Jiang, Panos Achlioptas, Niloy J. Mitra, and Leonidas J. Guibas. 2020 · 2020
Cited alongside, same era.
Deepmetahandles: Learning deformation meta-handles of 3d meshes with biharmonic coordinates
Minghua Liu, Minhyuk Sung, Radomir Mech, and Hao Su. 2021 · 2021
Cited alongside, same era.
StyleCLIP: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski. 2021 · 2021
Cited alongside, same era.
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 · 2021
Cited alongside, same era.
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. 2018a
Cited in the paper.
Isolating sources of disentanglement in vaes
Ricky T. Q. Chen, Xuechen Li, Roger Grosse, and David Duvenaud. 2018b
Cited in the paper.
Oscar Michel, Roi Bar-On, Richard Liu, Sagie Benaim, and Rana Hanocka. 2022 · 2022
Closest in time.
Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall. 2022 · 2022
Closest in time.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022
Closest in time.
CLIP-NeRF: Text-and-image driven manipulation of neural radiance fields
Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao. 2022 · 2022
Closest in time.
3D-Scene-Entities: Using phrase-to-3D-object correspondences for richer visio-linguistic models in 3D scenes
Anonymous. 2023 · 2023
Closest in time.