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Our work addresses limitations seen in previous approaches for object-centric editing problems, such as unrealistic results due to shape discrepancies and limited control in object replacement or insertion.
2018
Earlier work this paper cites.
Wu, Y., AbdAlmageed, W., Natarajan, P.: Mantra-net: Manipulation tracing network for detection and localization of image forgeries with anomalous features. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 9535–9544 (2019). https://doi.org/10.1109/CVPR.2019.00977
2019
Earlier work this paper cites.
Hu, X., Zhang, Z., Jiang, Z., Chaudhuri, S., Yang, Z., Nevatia, R.: Span: Spatial pyramid attention network for image manipulation localization. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXI 16. pp. 312–328. Springer (2020)
2020
Earlier work this paper cites.
Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. International Conference on Learning Representations (2020)
2020
Earlier work this paper cites.
Meng, C., He, Y., Song, Y., Song, J., Wu, J., Zhu, J.Y., Ermon, S.: Sdedit: Guided image synthesis and editing with stochastic differential equations. International Conference on Learning Representations (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.
Bar-Tal, O., Ofri-Amar, D., Fridman, R., Kasten, Y., Dekel, T.: Text2live: Text-driven layered image and video editing. In: European Conference on Computer Vision. pp. 707–723. Springer (2022)
2022
Earlier work this paper cites.
Hertz, A., Mokady, R., Tenenbaum, J., Aberman, K., Pritch, Y., Cohen-Or, D.: Prompt-to-prompt image editing with cross attention control. International Conference on Learning Representations (2022). https://doi.org/10.48550/arXiv.2208.01626
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
Earlier work this paper cites.
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E.L., Ghasemipour, S.K.S., Lopes, R.G., Ayan, B.K., Salimans, T., Ho, J., Fleet, D.J., Norouzi, M.: Photorealistic text-to-image diffusion models with deep language understanding. In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A. (eds.) Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022 (2022), http://papers.nips.cc/paper_files/paper/2022/hash/ec795aeadae0b7d230fa35cbaf04c041-Abstract-Conference.html
2022
Earlier work this paper cites.
Wang, J., Wu, Z., Chen, J., Han, X., Shrivastava, A., Lim, S.N., Jiang, Y.G.: Objectformer for image manipulation detection and localization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2364–2373 (2022)
2022
Earlier work this paper cites.
Agarwal, A., Karanam, S., Joseph, K., Saxena, A., Goswami, K., Srinivasan, B.V.: A-star: Test-time attention segregation and retention for text-to-image synthesis. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2283–2293 (2023)
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
Cited alongside, same era.
Cao, M., Wang, X., Qi, Z., Shan, Y., Qie, X., Zheng, Y.: Masactrl: Tuning-free mutual self-attention control for consistent image synthesis and editing. In: IEEE/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1-6, 2023. pp. 22503–22513. IEEE (2023). https://doi.org/10.1109/ICCV51070.2023.02062, https://doi.org/10.1109/ICCV51070.2023.02062
2023
Cited alongside, same era.
Tumanyan, N., Geyer, M., Bagon, S., Dekel, T.: Plug-and-play diffusion features for text-driven image-to-image translation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1921–1930 (2023)
2023
Later among the works it cites.
Tunstall, L., Beeching, E., Lambert, N., Rajani, N., Rasul, K., Belkada, Y., Huang, S., von Werra, L., Fourrier, C., Habib, N., Sarrazin, N., Sanseviero, O., Rush, A.M., Wolf, T.: Zephyr: Direct distillation of lm alignment. arXiv preprint arXiv: 2310.16944 (2023)
2023
Later among the works it cites.
Valevski, D., Kalman, M., Molad, E., Segalis, E., Matias, Y., Leviathan, Y.: Unitune: Text-driven image editing by fine tuning a diffusion model on a single image. ACM Trans. Graph. 42
2023
Later among the works it cites.
Wallace, B., Gokul, A., Naik, N.: Edict: Exact diffusion inversion via coupled transformations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 22532–22541 (2023)
2023
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2023
Cited alongside, same era.
Couairon, G., Verbeek, J., Schwenk, H., Cord, M.: Diffedit: Diffusion-based semantic image editing with mask guidance. In: The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net (2023), https://openreview.net/forum?id=3lge0p5o-M-
2023
Cited alongside, same era.
Epstein, D., Jabri, A., Poole, B., Efros, A.A., Holynski, A.: Diffusion self-guidance for controllable image generation. In: Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M., Levine, S. (eds.) Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 (2023), http://papers.nips.cc/paper_files/paper/2023/hash/3469b211b829b39d2b0cfd3b880a869c-Abstract-Conference.html
2023
Cited alongside, same era.
Hertz, A., Aberman, K., Cohen-Or, D.: Delta denoising score. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2328–2337 (2023)
2023
Cited alongside, same era.
Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I., Irani, M.: Imagic: Text-based real image editing with diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6007–6017 (2023)
2023
Cited alongside, same era.
Li, Y., Keuper, M., Zhang, D., Khoreva, A.: Divide & bind your attention for improved generative semantic nursing. In: 34th British Machine Vision Conference 2023, BMVC 2023 (2023)
2023
Cited alongside, same era.
Mokady, R., Hertz, A., Aberman, K., Pritch, Y., Cohen-Or, D.: Null-text inversion for editing real images using guided diffusion models. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17-24, 2023. pp. 6038–6047. IEEE (2023). https://doi.org/10.1109/CVPR52729.2023.00585, https://doi.org/10.1109/CVPR52729.2023.00585
2023
Cited alongside, same era.
Nguyen, Q.H., Vu, T.T., Tran, A.T., Nguyen, K.: Dataset diffusion: Diffusion-based synthetic data generation for pixel-level semantic segmentation. In: Thirty-seventh Conference on Neural Information Processing Systems (2023), https://openreview.net/forum?id=StD4J5ZlI5
2023
Cited alongside, same era.
Parmar, G., Kumar Singh, K., Zhang, R., Li, Y., Lu, J., Zhu, J.Y.: Zero-shot image-to-image translation. In: ACM SIGGRAPH 2023 Conference Proceedings. pp. 1–11 (2023)
2023
Cited alongside, same era.
Later among the works it cites.
Xie, J., Li, Y., Huang, Y., Liu, H., Zhang, W., Zheng, Y., Shou, M.Z.: Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 7452–7461 (2023)
2023
Later among the works it cites.
Zhang, K., Mo, L., Chen, W., Sun, H., Su, Y.: Magicbrush: A manually annotated dataset for instruction-guided image editing. Neural Information Processing Systems (2023). https://doi.org/10.48550/arXiv.2306.10012
2023
Later among the works it cites.
Zhang, Z., Han, L., Ghosh, A., Metaxas, D.N., Ren, J.: Sine: Single image editing with text-to-image diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6027–6037 (2023)
2023
Later among the works it cites.
Geng, Z., Yang, B., Hang, T., Li, C., Gu, S., Zhang, T., Bao, J., Zhang, Z., Li, H., Hu, H., et al.: Instructdiffusion: A generalist modeling interface for vision tasks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 12709–12720 (2024)
2024
Closest in time.
Ju, X., Zeng, A., Bian, Y., Liu, S., Xu, Q.: Pnp inversion: Boosting diffusion-based editing with 3 lines of code. In: The Twelfth International Conference on Learning Representations (2024)
2024
Closest in time.
Mirzaei, A., Aumentado-Armstrong, T., Brubaker, M.A., Kelly, J., Levinshtein, A., Derpanis, K.G., Gilitschenski, I.: Watch your steps: Local image and scene editing by text instructions. In: ECCV (2024)
2024
Closest in time.