[1] Ankan Kumar Bhunia, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan, Jorma Laaksonen, and Michael Felsberg. Doodleformer: Creative sketch drawing with transformers. In Proceedings of the European conference on computer vision (ECCV), pages 338-355, 2022.
[2] John Canny. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6):679–698, 1986.
[3] Caroline Chan, Frédo Durand, and Phillip Isola. Learning to generate line drawings that convey geometry and semantics. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 7915-7925, June 2022.
[4] Shu-Yu Chen, Wanchao Su, Lin Gao, Shihong Xia, and Hongbo Fu. Deepfacedrawing: Deep generation of face images from sketches. In ACM Transactions on Graphics (TOG), volume 39, pages 72-1. ACM New York, NY, USA, 2020.
[5] Prafulla Dhariwal and Alexander Nichol. Diffusion models beat gans on image synthesis. In Advances in Neural Information Processing Systems (NIPS), volume 34, pages 8780-8794, 2021.
[6] Patrick Esser, Robin Rombach, and Bjorn Ommer. Taming transformers for high-resolution image synthesis. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (NIPS), pages 12873-12883, 2021.
[7] Kevin Frans, Lisa Soros, and Olaf Witkowski. CLIPDraw: Exploring text-to-drawing synthesis through language-image encoders. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems (NIPS), 2022.
[8] Songwei Ge, Vedanuj Goswami, Larry Zitnick, and Devi Parikh. Creative sketch generation. In International Conference on Learning Representations (ICLR), 2021.
[9] David Ha and Douglas Eck. A neural representation of sketch drawings. In International Conference on Learning Representations (ICLR), 2018.
[10] Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-or. Prompt-to-prompt image editing with cross-attention control. In The Eleventh International Conference on Learning Representations (ICLR), 2023.
[11] Jonathan Ho, Ajay Jain, and Pieter Abbeel. Denoising diffusion probabilistic models. In Advances in Neural Information Processing Systems (NIPS), volume 33, pages 6840-6851, 2020.
[12] Jonathan Ho and Tim Salimans. Classifier-free diffusion guidance. arXiv preprint arXiv:2207.12598, 2022.
[13] Ajay Jain, Amber Xie, and Pieter Abbeel. Vectorfusion: Text-to-svg by abstracting pixel-based diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
[14] Dmytro Kotovenko, Matthias Wright, Arthur Heimbrecht, and Bjorn Ommer. Rethinking style transfer: From pixels to parameterized brushstrokes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 12196-12205, 2021.
[15] Mengtian Li, Zhe Lin, Radomir Mech, Ersin Yumer, and Deva Ramanan. Photo-sketching: Inferring contour drawings from images. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pages 1403-1412. IEEE, 2019.
[16] Tzu-Mao Li, Michal Lukáč, Gharbi Michael, and Jonathan Ragan-Kelley. Differentiable vector graphics rasterization for editing and learning. ACM Trans. Graph. (Proc. SIGGRAPH Asia), 39(6):193:1-193:15, 2020.
[17] Yi Li, Yi-Zhe Song, Timothy M Hospedales, and Shaogang Gong. Free-hand sketch synthesis with deformable stroke models. International Journal of Computer Vision, 122:169-190, 2017.