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We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only $1$ minute.The key component is a dual-mode multi-view latent diffusion model.
Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. and Ba, J · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P., and Brox, T · 2015
Earlier work this paper cites.
Ba, J. L., Kiros, J. R., and Hinton, G. E · 2016
Earlier work this paper cites.
Gaussian error linear units (gelus)
Hendrycks, D. and Gimpel, K · 2016
Earlier work this paper cites.
Accurate, large minibatch sgd: Training imagenet in 1 hour
Goyal, P., Dollár, P., Girshick, R., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y., and He, K · 2017
Earlier work this paper cites.
Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
Earlier work this paper cites.
Progressive growing of GANs for improved quality, stability, and variation
Karras, T., Aila, T., Laine, S., and Lehtinen, J · 2018
Earlier work this paper cites.
Group normalization
Wu, Y. and He, K · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
Earlier work this paper cites.
Generative adversarial networks
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2020
Earlier work this paper cites.
Analyzing and improving the image quality of stylegan
Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., and Aila, T · 2020
Earlier work this paper cites.
Modular primitives for high-performance differentiable rendering
Laine, S., Hellsten, J., Karras, T., Seol, Y., Lehtinen, J., and Aila, T · 2020
Earlier work this paper cites.
Neural sparse voxel fields
Liu, L., Gu, J., Zaw Lin, K., Chua, T.-S., and Theobalt, C · 2020
Earlier work this paper cites.
Graf: Generative radiance fields for 3d-aware image synthesis
Schwarz, K., Liao, Y., Niemeyer, M., and Geiger, A · 2020
Earlier work this paper cites.
pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
Chan, E. R., Monteiro, M., Kellnhofer, P., Wu, J., and Wetzstein, G · 2021
Earlier work this paper cites.
Stylenerf: A style-based 3d-aware generator for high-resolution image synthesis
Gu, J., Liu, L., Wang, P., and Theobalt, C · 2021
Earlier work this paper cites.
Alias-free generative adversarial networks
Karras, T., Aittala, M., Laine, S., Härkönen, E., Hellsten, J., Lehtinen, J., and Aila, T · 2021
Earlier work this paper cites.
Nerf: Representing scenes as neural radiance fields for view synthesis
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., and Ng, R · 2021
Earlier work this paper cites.
Benchmark for compositional text-to-image synthesis
Park, D. H., Azadi, S., Liu, X., Darrell, T., and Rohrbach, A · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
Cited alongside, same era.
Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
Reizenstein, J., Shapovalov, R., Henzler, P., Sbordone, L., Labatut, P., and Novotny, D · 2021
Cited alongside, same era.
Light field networks: Neural scene representations with single-evaluation rendering
Sitzmann, V., Rezchikov, S., Freeman, B., Tenenbaum, J., and Durand, F · 2021
Cited alongside, same era.
Denoising diffusion implicit models
Song, J., Meng, C., and Ermon, S · 2021
Cited alongside, same era.
Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Wang, P., Liu, L., Liu, Y., Theobalt, C., Komura, T., and Wang, W · 2021
Cited alongside, same era.
Objaverse: A universe of annotated 3d objects
Deitke, M., Schwenk, D., Salvador, J., Weihs, L., Michel, O., VanderBilt, E., Schmidt, L., Ehsani, K., Kembhavi, A., and Farhadi, A · 2023
Later among the works it cites.
Streetsurf: Extending multi-view implicit surface reconstruction to street views
Guo, J., Deng, N., Li, X., Bai, Y., Shi, B., Wang, C., Ding, C., Wang, D., and Li, Y · 2023
Later among the works it cites.
3dgen: Triplane latent diffusion for textured mesh generation
Gupta, A., Xiong, W., Nie, Y., Jones, I., and Oğuz, B · 2023
Later among the works it cites.
Lrm: Large reconstruction model for single image to 3d
Hong, Y., Zhang, K., Gu, J., Bi, S., Zhou, Y., Liu, D., Liu, F., Sunkavalli, K., Bui, T., and Tan, H · 2023
Later among the works it cites.
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Yariv, L., Gu, J., Kasten, Y., and Lipman, Y · 2021
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Efficient geometry-aware 3d generative adversarial networks
Chan, E. R., Lin, C. Z., Chan, M. A., Nagano, K., Pan, B., De Mello, S., Gallo, O., Guibas, L. J., Tremblay, J., Khamis, S., et al · 2022
Cited alongside, same era.
Tensorf: Tensorial radiance fields
Chen, A., Xu, Z., Geiger, A., Yu, J., and Su, H · 2022
Cited alongside, same era.
Gram: Generative radiance manifolds for 3d-aware image generation
Deng, Y., Yang, J., Xiang, J., and Tong, X · 2022
Cited alongside, same era.
Towards a unified view of parameter-efficient transfer learning
He, J., Zhou, C., Ma, X., Berg-Kirkpatrick, T., and Neubig, G · 2022
Cited alongside, same era.
LoRA: Low-rank adaptation of large language models
Hu, E. J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2022
Cited alongside, same era.
Zero-shot text-guided object generation with dream fields
Jain, A., Mildenhall, B., Barron, J. T., Abbeel, P., and Poole, B · 2022
Cited alongside, same era.
Jun, H. and Nichol, A · 2023
Later among the works it cites.
Katzir, O., Patashnik, O., Cohen-Or, D., and Lischinski, D · 2023
Later among the works it cites.
3d gaussian splatting for real-time radiance field rendering
Kerbl, B., Kopanas, G., Leimkühler, T., and Drettakis, G · 2023
Later among the works it cites.
Magic3d: High-resolution text-to-3d content creation
Lin, C.-H., Gao, J., Tang, L., Takikawa, T., Zeng, X., Huang, X., Kreis, K., Fidler, S., Liu, M.-Y., and Lin, T.-Y · 2023
Later among the works it cites.
Dl3dv-10k: A large-scale scene dataset for deep learning-based 3d vision
Ling, L., Sheng, Y., Tu, Z., Zhao, W., Xin, C., Wan, K., Yu, L., Guo, Q., Yu, Z., Lu, Y., et al · 2023
Later among the works it cites.
Wonder3d: Single image to 3d using cross-domain diffusion
Long, X., Guo, Y.-C., Lin, C., Liu, Y., Dou, Z., Liu, L., Ma, Y., Zhang, S.-H., Habermann, M., Theobalt, C., et al · 2023
Later among the works it cites.
Scalable 3d captioning with pretrained models
Luo, T., Rockwell, C., Lee, H., and Johnson, J · 2023
Later among the works it cites.
Scalable diffusion models with transformers
Peebles, W. and Xie, S · 2023
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Mvdream: Multi-view diffusion for 3d generation
Shi, Y., Wang, P., Ye, J., Mai, L., Li, K., and Yang, X · 2023
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3d neural field generation using triplane diffusion
Shue, J. R., Chan, E. R., Po, R., Ankner, Z., Wu, J., and Wetzstein, G · 2023
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Textmesh: Generation of realistic 3d meshes from text prompts
Tsalicoglou, C., Manhardt, F., Tonioni, A., Niemeyer, M., and Tombari, F · 2023
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Gram-hd: 3d-consistent image generation at high resolution with generative radiance manifolds
Xiang, J., Yang, J., Deng, Y., and Tong, X · 2023
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Dmv3d: Denoising multi-view diffusion using 3d large reconstruction model
Xu, Y., Tan, H., Luan, F., Bi, S., Wang, P., Li, J., Shi, Z., Sunkavalli, K., Wetzstein, G., Xu, Z., et al · 2023
Later among the works it cites.
Mvimgnet: A large-scale dataset of multi-view images
Yu, X., Xu, M., Zhang, Y., Liu, H., Ye, C., Wu, Y., Yan, Z., Zhu, C., Xiong, Z., Liang, T., et al · 2023
Later among the works it cites.
Sparse3d: Distilling multiview-consistent diffusion for object reconstruction from sparse views
Zou, Z.-X., Cheng, W., Cao, Y.-P., Huang, S.-S., Shan, Y., and Zhang, S.-H · 2023
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Hd-fusion: Detailed text-to-3d generation leveraging multiple noise estimation
Wu, J., Gao, X., Liu, X., Shen, Z., Zhao, C., Feng, H., Liu, J., and Ding, E · 2024
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