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Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D objects.
Nicodemus, F.E.: Directional reflectance and emissivity of an opaque surface. Applied optics 4
1965
Earlier work this paper cites.
Burley, B., Studios, W.D.A.: Physically-based shading at disney. In: Acm Siggraph. vol. 2012, pp. 1–7. vol. 2012 (2012)
2012
Earlier work this paper cites.
Aittala, M., Weyrich, T., Lehtinen, J.: Practical svbrdf capture in the frequency domain. ACM Trans. Graph. 32
2013
Earlier work this paper cites.
Karis, B., Games, E.: Real shading in unreal engine 4. Proc. Physically Based Shading Theory Practice 4
2013
Earlier work this paper cites.
Nam, G., Lee, J.H., Gutierrez, D., Kim, M.H.: Practical svbrdf acquisition of 3d objects with unstructured flash photography. ACM Transactions on Graphics (TOG) 37
2018
Earlier work this paper cites.
Gao, D., Li, X., Dong, Y., Peers, P., Xu, K., Tong, X.: Deep inverse rendering for high-resolution svbrdf estimation from an arbitrary number of images. ACM Trans. Graph. 38
2019
Earlier work this paper cites.
Mildenhall, B., Srinivasan, P.P., Tancik, M., Barron, J.T., Ramamoorthi, R., Ng, R.: Nerf: Representing scenes as neural radiance fields for view synthesis. Communications of the ACM 65
2021
Earlier work this paper cites.
Park, D.H., Azadi, S., Liu, X., Darrell, T., Rohrbach, A.: Benchmark for compositional text-to-image synthesis. In: Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1) (2021)
2021
Earlier work this paper cites.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: International conference on machine learning. pp. 8748–8763. PMLR (2021)
2021
Earlier work this paper cites.
Shen, T., Gao, J., Yin, K., Liu, M.Y., Fidler, S.: Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis. Advances in Neural Information Processing Systems 34
2021
Earlier work this paper cites.
Srinivasan, P.P., Deng, B., Zhang, X., Tancik, M., Mildenhall, B., Barron, J.T.: Nerv: Neural reflectance and visibility fields for relighting and view synthesis. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7495–7504 (2021)
2021
Earlier work this paper cites.
Zhang, X., Srinivasan, P.P., Deng, B., Debevec, P., Freeman, W.T., Barron, J.T.: Nerfactor: Neural factorization of shape and reflectance under an unknown illumination. ACM Transactions on Graphics (ToG) 40
2021
Earlier work this paper cites.
2022
Earlier work this paper cites.
Hessel, J., Holtzman, A., Forbes, M., Bras, R.L., Choi, Y.: Clipscore: A reference-free evaluation metric for image captioning (2022)
2022
Earlier work this paper cites.
Hui, K.H., Li, R., Hu, J., Fu, C.W.: Neural wavelet-domain diffusion for 3d shape generation. In: SIGGRAPH Asia 2022 Conference Papers. pp. 1–9 (2022)
2022
Earlier work this paper cites.
Jain, A., Mildenhall, B., Barron, J.T., Abbeel, P., Poole, B.: Zero-shot text-guided object generation with dream fields. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 867–876 (2022)
2022
Earlier work this paper cites.
Mohammad Khalid, N., Xie, T., Belilovsky, E., Popa, T.: Clip-mesh: Generating textured meshes from text using pretrained image-text models. In: SIGGRAPH Asia 2022 conference papers. pp. 1–8 (2022)
2022
Earlier work this paper cites.
Munkberg, J., Hasselgren, J., Shen, T., Gao, J., Chen, W., Evans, A., Müller, T., Fidler, S.: Extracting triangular 3d models, materials, and lighting from images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8280–8290 (2022)
2022
Earlier work this paper cites.
Munkberg, J., Hasselgren, J., Shen, T., Gao, J., Chen, W., Evans, A., Müller, T., Fidler, S.: Extracting Triangular 3D Models, Materials, and Lighting From Images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 8280–8290 (June 2022)
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10684–10695 (2022)
2022
Cited alongside, same era.
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.: Photorealistic text-to-image diffusion models with deep language understanding. Advances in Neural Information Processing Systems 35
2022
Cited alongside, same era.
Chen, F.L., Zhang, D.Z., Han, M.L., Chen, X.Y., Shi, J., Xu, S., Xu, B.: Vlp: A survey on vision-language pre-training. Machine Intelligence Research 20
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Closest in time.
Wiig, T.: Blur latent noise. https://gist.github.com/ trygvebw/e51573d40841d22c11fc32df6863ef58 (2023)
2023
Closest in time.
Wu, J.Z., Ge, Y., Wang, X., Lei, S.W., Gu, Y., Shi, Y., Hsu, W., Shan, Y., Qie, X., Shou, M.Z.: Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7623–7633 (2023)
2023
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Xu, J., Wang, X., Cheng, W., Cao, Y.P., Shan, Y., Qie, X., Gao, S.: Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 20908–20918 (2023)
2023
Closest in time.
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Chen, R., Chen, Y., Jiao, N., Jia, K.: Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) (October 2023)
2023
Cited alongside, same era.
Cheng, Y.C., Lee, H.Y., Tulyakov, S., Schwing, A.G., Gui, L.Y.: Sdfusion: Multimodal 3d shape completion, reconstruction, and generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4456–4465 (2023)
2023
Cited alongside, same era.
2023
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2023
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2023
Cited alongside, same era.
Lin, C.H., Gao, J., Tang, L., Takikawa, T., Zeng, X., Huang, X., Kreis, K., Fidler, S., Liu, M.Y., Lin, T.Y.: Magic3d: High-resolution text-to-3d content creation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 300–309 (2023)
2023
Cited alongside, same era.
Liu, R., Wu, R., Van Hoorick, B., Tokmakov, P., Zakharov, S., Vondrick, C.: Zero-1-to-3: Zero-shot one image to 3d object. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 9298–9309 (2023)
2023
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2023
Closest in time.
Yu, C., Zhou, Q., Li, J., Zhang, Z., Wang, Z., Wang, F.: Points-to-3d: Bridging the gap between sparse points and shape-controllable text-to-3d generation. In: Proceedings of the 31st ACM International Conference on Multimedia. pp. 6841–6850 (2023)
2023
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2024
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Liu, F., Wu, D., Wei, Y., Rao, Y., Duan, Y.: Sherpa3d: Boosting high-fidelity text-to-3d generation via coarse 3d prior. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 20763–20774 (2024)
2024
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Qiu, L., Chen, G., Gu, X., Zuo, Q., Xu, M., Wu, Y., Yuan, W., Dong, Z., Bo, L., Han, X.: Richdreamer: A generalizable normal-depth diffusion model for detail richness in text-to-3d. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9914–9925 (2024)
2024
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Zou, Z.X., Yu, Z., Guo, Y.C., Li, Y., Liang, D., Cao, Y.P., Zhang, S.H.: Triplane meets gaussian splatting: Fast and generalizable single-view 3d reconstruction with transformers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10324–10335 (2024)
2024
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