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Recent advancements in automatic 3D avatar generation guided by text have made significant progress.
On information and sufficiency
Kullback, S. and Leibler, R. A · 1951
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Bayesian learning via stochastic gradient langevin dynamics
Welling, M. and Teh, Y. W · 2011
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Smpl: A skinned multi-person linear model
Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., and Black, M. J · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Densepose: Dense human pose estimation in the wild
Güler, R. A., Neverova, N., and Kokkinos, I · 2018
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Deepsdf: Learning continuous signed distance functions for shape representation
Park, J. J., Florence, P., Straub, J., Newcombe, R., and Lovegrove, S · 2019
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Pytorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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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.
Volumetric human teleportation
Li, R., Olszewski, K., Xiu, Y., Saito, S., Huang, Z., and Li, H · 2020
Earlier work this paper cites.
Monocular real-time volumetric performance capture
Li, R., Xiu, Y., Saito, S., Huang, Z., Olszewski, K., and Li, H · 2020
Earlier work this paper cites.
Zhu, L., Rematas, K., Curless, B., Seitz, S. M., and Kemelmacher-Shlizerman, I · 2020
Earlier work this paper cites.
imghum: Implicit generative models of 3d human shape and articulated pose
Alldieck, T., Xu, H., and Sminchisescu, C · 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.
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
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Self-supervised collision handling via generative 3d garment models for virtual try-on
Santesteban, I., Thuerey, N., Otaduy, M. A., and Casas, D · 2021
Earlier work this paper cites.
Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis
Shen, T., Gao, J., Yin, K., Liu, M.-Y., and Fidler, 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.
Deepmulticap: Performance capture of multiple characters using sparse multiview cameras
Zheng, Y., Shao, R., Zhang, Y., Yu, T., Zheng, Z., Dai, Q., and Liu, Y · 2021
Cited alongside, same era.
Avatarclip: Zero-shot text-driven generation and animation of 3d avatars
Hong, F., Zhang, M., Pan, L., Cai, Z., Yang, L., and Liu, Z · 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.
Dreamavatar: Text-and-shape guided 3d human avatar generation via diffusion models
Cao, Y., Cao, Y.-P., Han, K., Shan, Y., and Wong, K.-Y. K · 2023
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Reproducible scaling laws for contrastive language-image learning
Cherti, M., Beaumont, R., Wightman, R., Wortsman, M., Ilharco, G., Gordon, C., Schuhmann, C., Schmidt, L., and Jitsev, J · 2023
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High-fidelity 3d human digitization from single 2k resolution images
Han, S.-H., Park, M.-G., Yoon, J. H., Kang, J.-M., Park, Y.-J., and Jeon, H.-G · 2023
Later among the works it cites.
Avatarcraft: Transforming text into neural human avatars with parameterized shape and pose control
Jiang, R., Wang, C., Zhang, J., Chai, M., He, M., Chen, D., and Liao, J · 2023
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3d gaussian splatting for real-time radiance field rendering
Kerbl, B., Kopanas, G., Leimkühler, T., and Drettakis, G · 2023
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Jiang, W., Yi, K. M., Samei, G., Tuzel, O., and Ranjan, A · 2022
Cited alongside, same era.
X-clip: End-to-end multi-grained contrastive learning for video-text retrieval
Ma, Y., Xu, G., Sun, X., Yan, M., Zhang, J., and Ji, R · 2022
Cited alongside, same era.
Clip-mesh: Generating textured meshes from text using pretrained image-text models
Mohammad Khalid, N., Xie, T., Belilovsky, E., and Popa, T · 2022
Cited alongside, same era.
Dreamfusion: Text-to-3d using 2d diffusion
Poole, B., Jain, A., Barron, J. T., and Mildenhall, B · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., and Ommer, B · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E. L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al · 2022
Cited alongside, same era.
Clip-forge: Towards zero-shot text-to-shape generation
Sanghi, A., Chu, H., Lambourne, J. G., Wang, Y., Cheng, C.-Y., Fumero, M., and Malekshan, K. R · 2022
Cited alongside, same era.
Sinddm: A single image denoising diffusion model
Kulikov, V., Yadin, S., Kleiner, M., and Michaeli, T · 2023
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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.
Humangaussian: Text-driven 3d human generation with gaussian splatting
Liu, X., Zhan, X., Tang, J., Shan, Y., Zeng, G., Lin, D., Liu, X., and Liu, Z · 2023
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Dreamgaussian: Generative gaussian splatting for efficient 3d content creation
Tang, J., Ren, J., Zhou, H., Liu, Z., and Zeng, G · 2023
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Econ: Explicit clothed humans optimized via normal integration
Xiu, Y., Yang, J., Cao, X., Tzionas, D., and Black, M. J · 2023
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Gaussiandreamer: Fast generation from text to 3d gaussian splatting with point cloud priors
Yi, T., Fang, J., Wu, G., Xie, L., Zhang, X., Liu, W., Tian, Q., and Wang, X · 2023
Later among the works it cites.
Avatarbooth: High-quality and customizable 3d human avatar generation
Zeng, Y., Lu, Y., Ji, X., Yao, Y., Zhu, H., and Cao, X · 2023
Later among the works it cites.
Dreamhuman: Animatable 3d avatars from text
Kolotouros, N., Alldieck, T., Zanfir, A., Bazavan, E., Fieraru, M., and Sminchisescu, C · 2024
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En3d: An enhanced generative model for sculpting 3d humans from 2d synthetic data
Men, Y., Lei, B., Yao, Y., Cui, M., Lian, Z., and Xie, X · 2024
Closest in time.
Avatarverse: High-quality & stable 3d avatar creation from text and pose
Zhang, H., Chen, B., Yang, H., Qu, L., Wang, X., Chen, L., Long, C., Zhu, F., Du, D., and Zheng, M · 2024
Closest in time.
Headstudio: Text to animatable head avatars with 3d gaussian splatting
Zhou, Z., Ma, F., Fan, H., and Yang, Y · 2024
Closest in time.