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We propose ZeST, a method for zero-shot material transfer to an object in the input image given a material exemplar image.
Khan, E.A., Reinhard, E., Fleming, R.W., Bülthoff, H.H.: Image-based material editing. ACM Transactions on Graphics (TOG) 25
2006
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Aittala, M., Weyrich, T., Lehtinen, J.: Practical svbrdf capture in the frequency domain. ACM Trans. Graph. 32
2013
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Aittala, M., Weyrich, T., Lehtinen, J., et al.: Two-shot svbrdf capture for stationary materials. ACM Trans. Graph. 34
2015
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Bell, S., Upchurch, P., Snavely, N., Bala, K.: Material recognition in the wild with the materials in context database. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3479–3487 (2015)
2015
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Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 586–595 (2018)
2018
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Deschaintre, V., Aittala, M., Durand, F., Drettakis, G., Bousseau, A.: Flexible svbrdf capture with a multi-image deep network. In: Computer graphics forum. vol. 38, pp. 1–13. Wiley Online Library (2019)
2019
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Song, Y., Ermon, S.: Generative modeling by estimating gradients of the data distribution. Advances in neural information processing systems 32
2019
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Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial networks. Communications of the ACM 63
2020
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Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Advances in neural information processing systems 33
2020
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Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. Advances in neural information processing systems 34
2021
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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
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Ranftl, R., Bochkovskiy, A., Koltun, V.: Vision transformers for dense prediction. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 12179–12188 (2021)
2021
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Delanoy, J., Lagunas, M., Condor, J., Gutierrez, D., Masia, B.: A generative framework for image-based editing of material appearance using perceptual attributes. In: Computer Graphics Forum. vol. 41, pp. 453–464. Wiley Online Library (2022)
2022
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2022
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Ho, J., Saharia, C., Chan, W., Fleet, D.J., Norouzi, M., Salimans, T.: Cascaded diffusion models for high fidelity image generation. The Journal of Machine Learning Research 23
2022
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Ho, J., Salimans, T.: Classifier-free diffusion guidance. arXiv preprint arXiv:2207.12598 (2022)
2022
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Karras, T., Aittala, M., Aila, T., Laine, S.: Elucidating the design space of diffusion-based generative models. Advances in Neural Information Processing Systems 35
2022
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Liang, Y., Wakaki, R., Nobuhara, S., Nishino, K.: Multimodal material segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 19800–19808 (2022)
2022
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2022
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Upchurch, P., Niu, R.: A dense material segmentation dataset for indoor and outdoor scene parsing. In: European Conference on Computer Vision. pp. 450–466. Springer (2022)
2022
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Bar-Tal, O., Yariv, L., Lipman, Y., Dekel, T.: Multidiffusion: Fusing diffusion paths for controlled image generation (2023)
2023
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2023
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2023
Later among the works it cites.
2023
Later among the works it cites.
Sharma, P., Philip, J., Gharbi, M., Freeman, B., Durand, F., Deschaintre, V.: Materialistic: Selecting similar materials in images. ACM Transactions on Graphics (TOG) 42
2023
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2023
Cited alongside, same era.
Brooks, T., Holynski, A., Efros, A.A.: Instructpix2pix: Learning to follow image editing instructions. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 18392–18402 (2023)
2023
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2023
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Cao, T., Kreis, K., Fidler, S., Sharp, N., Yin, K.: Texfusion: Synthesizing 3d textures with text-guided image diffusion models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4169–4181 (2023)
2023
Cited alongside, same era.
2023
Cited alongside, same era.
Deitke, M., Schwenk, D., Salvador, J., Weihs, L., Michel, O., VanderBilt, E., Schmidt, L., Ehsani, K., Kembhavi, A., Farhadi, A.: Objaverse: A universe of annotated 3d objects. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13142–13153 (2023)
2023
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Ge, S., Park, T., Zhu, J.Y., Huang, J.B.: Expressive text-to-image generation with rich text. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7545–7556 (2023)
2023
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Kang, M., Zhu, J.Y., Zhang, R., Park, J., Shechtman, E., Paris, S., Park, T.: Scaling up gans for text-to-image synthesis. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10124–10134 (2023)
2023
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Subias, J.D., Lagunas, M.: In-the-wild material appearance editing using perceptual attributes. In: Computer Graphics Forum. vol. 42, pp. 333–345. Wiley Online Library (2023)
2023
Later among the works it cites.
2023
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Yang, Z., Wang, J., Gan, Z., Li, L., Lin, K., Wu, C., Duan, N., Liu, Z., Liu, C., Zeng, M., et al.: Reco: Region-controlled text-to-image generation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 14246–14255 (2023)
2023
Later among the works it cites.
2023
Later among the works it cites.
Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 3836–3847 (2023)
2023
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Chen, M., Laina, I., Vedaldi, A.: Training-free layout control with cross-attention guidance. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 5343–5353 (2024)
2024
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Chen, W., Hu, H., Li, Y., Ruiz, N., Jia, X., Chang, M.W., Cohen, W.W.: Subject-driven text-to-image generation via apprenticeship learning. Advances in Neural Information Processing Systems 36
2024
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2024
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Corneanu, C., Gadde, R., Martinez, A.M.: Latentpaint: Image inpainting in latent space with diffusion models. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 4334–4343 (2024)
2024
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Michel, O., Bhattad, A., VanderBilt, E., Krishna, R., Kembhavi, A., Gupta, T.: Object 3dit: Language-guided 3d-aware image editing. Advances in Neural Information Processing Systems 36
2024
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2024
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2024
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Zhao, S., Chen, D., Chen, Y.C., Bao, J., Hao, S., Yuan, L., Wong, K.Y.K.: Uni-controlnet: All-in-one control to text-to-image diffusion models. Advances in Neural Information Processing Systems 36
2024
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