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Text-to-3D generation has achieved significant success by incorporating powerful 2D diffusion models, but insufficient 3D prior knowledge also leads to the inconsistency of 3D geometry.
Accelerating large-scale inference with anisotropic vector quantization
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Denoising diffusion implicit models
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Score-based generative modeling through stochastic differential equations
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Stein variational gradient descent: A general purpose bayesian inference algorithm
Liu, Q. and Wang, D · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
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A unified particle-optimization framework for scalable bayesian sampling
Chen, C., Zhang, R., Wang, W., Li, B., and Chen, L · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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Text2shape: Generating shapes from natural language by learning joint embeddings
Chen, K., Choy, C. B., Savva, M., Chang, A. X., Funkhouser, T., and Savarese, S · 2019
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Function space particle optimization for bayesian neural networks
Wang, Z., Ren, T., Zhu, J., and Zhang, B · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Retrievegan: Image synthesis via differentiable patch retrieval
Tseng, H.-Y., Lee, H.-Y., Jiang, L., Yang, M.-H., and Yang, W · 2020
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Synsin: End-to-end view synthesis from a single image
Wiles, O., Gkioxari, G., Szeliski, R., and Johnson, J · 2020
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Instance-conditioned gan
Casanova, A., Careil, M., Verbeek, J., Drozdzal, M., and Romero Soriano, A · 2021
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Lora: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2021
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Openclip, July 2021
Ilharco, G., Wortsman, M., Wightman, R., Gordon, C., Carlini, N., Taori, R., Dave, A., Shankar, V., Namkoong, H., Miller, J., Hajishirzi, H., Farhadi, A., and Schmidt, L · 2021
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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
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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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Geometry-free view synthesis: Transformers and no 3d priors
Rombach, R., Esser, P., and Ommer, B · 2021
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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
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Learned initializations for optimizing coordinate-based neural representations
Tancik, M., Mildenhall, B., Wang, T., Schmidt, D., Srinivasan, P. P., Barron, J. T., and Ng, R · 2021
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Plenoxels: Radiance fields without neural networks
Yu, A., Fridovich-Keil, S., Tancik, M., Chen, Q., Recht, B., and Kanazawa, A · 2021
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3d shape generation and completion through point-voxel diffusion
Zhou, L., Du, Y., and Wu, J · 2021
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threestudio: A unified framework for 3d content generation
Guo, Y.-C., Liu, Y.-T., Shao, R., Laforte, C., Voleti, V., Luo, G., Chen, C.-H., Zou, Z.-X., Wang, C., Cao, Y.-P., and Zhang, S.-H · 2023
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Animate-a-story: Storytelling with retrieval-augmented video generation
He, Y., Xia, M., Chen, H., Cun, X., Gong, Y., Xing, J., Zhang, Y., Wang, X., Weng, C., Shan, Y., et al · 2023
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Hertz, A., Aberman, K., and Cohen-Or, D · 2023
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Debiasing scores and prompts of 2d diffusion for robust text-to-3d generation
Hong, S., Ahn, D., and Kim, S · 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
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Blattmann, A., Rombach, R., Oktay, K., Müller, J., and Ommer, B · 2022
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Improving language models by retrieving from trillions of tokens
Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., Van Den Driessche, G. B., Lespiau, J.-B., Damoc, B., Clark, A., et al · 2022
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Particle-based variational inference with preconditioned functional gradient flow
Dong, H., Wang, X., Lin, Y., and Zhang, T · 2022
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Geometry in sampling methods: A review on manifold mcmc and particle-based variational inference methods
Liua, C. and Zhub, J · 2022
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Instant neural graphics primitives with a multiresolution hash encoding
Müller, T., Evans, A., Schied, C., and Keller, A · 2022
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Dreamfusion: Text-to-3d using 2d diffusion
Poole, B., Jain, A., Barron, J. T., and Mildenhall, B · 2022
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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
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Zero-1-to-3: Zero-shot one image to 3d object
Liu, R., Wu, R., Van Hoorick, B., Tokmakov, P., Zakharov, S., and Vondrick, C · 2023
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Scalable 3d captioning with pretrained models
Luo, T., Rockwell, C., Lee, H., and Johnson, J · 2023
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Latent-nerf for shape-guided generation of 3d shapes and textures
Metzer, G., Richardson, E., Patashnik, O., Giryes, R., and Cohen-Or, D · 2023
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Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors
Qian, G., Mai, J., Hamdi, A., Ren, J., Siarohin, A., Li, B., Lee, H.-Y., Skorokhodov, I., Wonka, P., Tulyakov, S., et al · 2023
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Low-rank adaptation for fast text-to-image diffusion fine-tuning
Ryu, S · 2023
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Let 2d diffusion model know 3d-consistency for robust text-to-3d generation
Seo, J., Jang, W., Kwak, M.-S., Ko, J., Kim, H., Kim, J., Kim, J.-H., Lee, J., and Kim, S · 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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Novel view synthesis with diffusion models
Watson, D., Chan, W., Brualla, R. M., Ho, J., Tagliasacchi, A., and Norouzi, M · 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
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Text-to-3d with classifier score distillation
Yu, X., Guo, Y.-C., Li, Y., Liang, D., Zhang, S.-H., and Qi, X · 2023
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Remodiffuse: Retrieval-augmented motion diffusion model
Zhang, M., Guo, X., Pan, L., Cai, Z., Hong, F., Li, H., Yang, L., and Liu, Z · 2023
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Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhou, Z. and Tulsiani, S · 2023
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