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Although recent advancements in text-to-3D generation have significantly improved generation quality, issues like limited level of detail and low fidelity still persist, which requires further improvement.
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Chen, Y., Zhang, C., Yang, X., Cai, Z., Yu, G., Yang, L., Lin, G.: It3D: Improved text-to-3D generation with explicit view synthesis. In: AAAI (2024)
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Chen, Z., Wang, F., Wang, Y., Liu, H.: Text-to-3D using gaussian splatting. In: IEEE Conf. Comput. Vis. Pattern Recog. (2024)
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Tsalicoglou, C., Manhardt, F., Tonioni, A., Niemeyer, M., Tombari, F.: Textmesh: Generation of realistic 3D meshes from text prompts. In: Int. Conf. on 3D Vision (3DV) (2024)
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Wang, Z., Lu, C., Wang, Y., Bao, F., Li, C., Su, H., Zhu, J.: Prolificdreamer: High-fidelity and diverse text-to-3D generation with variational score distillation. Adv. Neural Inform. Process. Syst. (2024)
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Yi, T., Fang, J., Wu, G., Xie, L., Zhang, X., Liu, W., Tian, Q., Wang, X.: Gaussiandreamer: Fast generation from text to 3D gaussian splatting with point cloud priors. IEEE Conf. Comput. Vis. Pattern Recog. (2024)
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