[47] T. Park, M.-Y. Liu, T.-C. Wang, and J.-Y. Zhu. Semantic image synthesis with spatially-adaptive normalization. In Proc. of Computer Vision and Pattern Recognition, 2019.
[48] D. Pathak, P. Krahenbuhl, J. Donahue, T. Darrell, and A. A. Efros. Context encoders: Feature learning by inpainting. In Proc. of Computer Vision and Pattern Recognition, 2016.
[49] D. Pavllo, A. Lucchi, and T. Hofmann. Controlling style and semantics in weakly-supervised image generation. In Proc. of European Conference on Computer Vision, 2020.
[50] A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen. Hierarchical text-conditional image generation with CLIP latents. arXiv preprint arXiv:2204.06125, 2022.
[51] A. Ramesh, M. Pavlov, G. Goh, S. Gray, C. Voss, A. Radford, M. Chen, and I. Sutskever. Zero-shot text-to-image generation. In Proc. of International Conference on Machine Learning, 2021.
[52] R. Ranftl, A. Bochkovskiy, and V. Koltun. Vision transformers for dense prediction. In Proc. of International Conference on Computer Vision, 2021.
[53] R. Ranftl, K. Lasinger, D. Hafner, K. Schindler, and V. Koltun. Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(3):1623-1637, 2020.
[54] Y. Ren, X. Fan, G. Li, S. Liu, and T. H. Li. Neural texture extraction and distribution for controllable person image synthesis. In Proc. of Computer Vision and Pattern Recognition, 2022.
[55] R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer. High-resolution image synthesis with latent diffusion models. In Proc. of Computer Vision and Pattern Recognition, 2022.
[56] C. Sahara, W. Chan, S. Saxena, L. Li, J. Whang, E. L. Denton, K. Ghasemipour, R. Gontijo Lopes, B. Karagol Ayan, T. Salimans, et al. Photorealistic text-to-image diffusion models with deep language understanding. Proc. of Advances in Neural Information Processing Systems, 2022.
[57] S. Song and T. Funkhouser. Neural Illumination: Lighting prediction for indoor environments. In Proc. of Computer Vision and Pattern Recognition, 2019.
[58] J. Sun, S. Weng, Z. Chang, S. Li, and B. Shi. UniCoRN: A unified conditional image repainting network. In Proc. of Computer Vision and Pattern Recognition, 2022.
[59] K. Sunkavalli, M. K. Johnson, W. Matusik, and H. Pfister. Multi-scale image harmonization. ACM Transactions on Graphics (Proc. of ACM SIGGRAPH), 29(4):1-10, 2010.
[60] J. Tang, Y. Zhu, H. Wang, J.-H. Chan, S. Li, and B. Shi. Estimating spatially-varying lighting in urban scenes with disentangled representation. In Proc. of European Conference on Computer Vision, 2022.
[61] S. Tripathi, S. Chandra, A. Agrawal, A. Tyagi, J. M. Rehg, and V. Chari. Learning to generate synthetic data via compositing. In Proc. of Computer Vision and Pattern Recognition, 2019.
[62] Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu, and M.-H. Yang. Deep image harmonization. In Proc. of Computer Vision and Pattern Recognition, 2017.
[63] Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600-612, 2004.
[64] Z. Wang, W. Chen, D. Acuna, J. Kautz, and S. Fidler. Neural light field estimation for street scenes with differentiable virtual object insertion. In Proc. of European Conference on Computer Vision, 2022.
[65] Z. Wang, X. Qi, K. Yuan, and M. Sun. Self-supervised correlation mining network for person image generation. In Proc. of Computer Vision and Pattern Recognition, 2022.
[66] S. Weng, W. Li, D. Li, H. Jin, and B. Shi. Conditional image inpainting via semantic bridge and piecewise value function. In Proc. of European Conference on Computer Vision, 2020.
[67] S. Weng, W. Li, D. Li, H. Jin, and B. Shi. MISC: Multi-condition injection and spatially-adaptive compositing for conditional person image synthesis. In Proc. of Computer Vision and Pattern Recognition, 2020.
[68] S. Weng, J. Sun, Y. Li, S. Li, and B. Shi.  $\mathrm{CT^2}$ : Colorization transformer via color tokens. In Proc. of European Conference on Computer Vision, 2022.