Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation N Ruiz, Y Li, V Jampani, Y Pritch, M Rubinstein, K Aberman Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 1497 | 2023 |
Measuring visual clutter R Rosenholtz, Y Li, L Nakano Journal of vision 7 (2), 17-17, 2007 | 947 | 2007 |
Principal components as a measure of systemic risk M Kritzman, Y Li, S Page, R Rigobon Available at SSRN 1582687, 2010 | 453 | 2010 |
Feature congestion: a measure of display clutter R Rosenholtz, Y Li, J Mansfield, Z Jin Proceedings of the SIGCHI conference on Human factors in computing systems …, 2005 | 434 | 2005 |
Removing photography artifacts using gradient projection and flash-exposure sampling A Agrawal, R Raskar, SK Nayar, Y Li ACM SIGGRAPH 2005 Papers, 828-835, 2005 | 421 | 2005 |
Compressing and companding high dynamic range images with subband architectures Y Li, L Sharan, EH Adelson ACM transactions on graphics (TOG) 24 (3), 836-844, 2005 | 358 | 2005 |
Muse: Text-to-image generation via masked generative transformers H Chang, H Zhang, J Barber, AJ Maschinot, J Lezama, L Jiang, MH Yang, ... arXiv preprint arXiv:2301.00704, 2023 | 321 | 2023 |
Skulls, financial turbulence, and risk management M Kritzman, Y Li Financial Analysts Journal 66 (5), 30-41, 2010 | 279 | 2010 |
Diffuse-specular separation and depth recovery from image sequences S Lin, Y Li, SB Kang, X Tong, HY Shum Computer Vision—ECCV 2002: 7th European Conference on Computer Vision …, 2002 | 208 | 2002 |
Image statistics for surface reflectance perception L Sharan, Y Li, I Motoyoshi, S Nishida, EH Adelson JOSA A 25 (4), 846-865, 2008 | 150 | 2008 |
Dreambooth3d: Subject-driven text-to-3d generation A Raj, S Kaza, B Poole, M Niemeyer, N Ruiz, B Mildenhall, S Zada, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 132 | 2023 |
Method and apparatus for acquiring HDR flash images R Raskar, A Agrawal, SK Nayar, Y Li US Patent 7,454,136, 2008 | 109 | 2008 |
Multiple-cue illumination estimation in textured scenes Y Li, H Lu, HY Shum Proceedings Ninth IEEE International Conference on Computer Vision, 1366-1373, 2003 | 91 | 2003 |
ScribbleBoost: Adding Classification to Edge‐Aware Interpolation of Local Image and Video Adjustments Y Li, E Adelson, A Agarwala Computer Graphics Forum 27 (4), 1255-1264, 2008 | 75 | 2008 |
Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models N Ruiz, Y Li, V Jampani, W Wei, T Hou, Y Pritch, N Wadhwa, M Rubinstein, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 73 | 2024 |
Lumiere: A space-time diffusion model for video generation O Bar-Tal, H Chefer, O Tov, C Herrmann, R Paiss, S Zada, A Ephrat, J Hur, ... arXiv preprint arXiv:2401.12945, 2024 | 64 | 2024 |
Samurai: Shape and material from unconstrained real-world arbitrary image collections M Boss, A Engelhardt, A Kar, Y Li, D Sun, J Barron, H Lensch, V Jampani Advances in Neural Information Processing Systems 35, 26389-26403, 2022 | 56 | 2022 |
Method for estimating camera settings adaptively R Raskar, A Agrawal, SK Nayar, Y Li US Patent 7,403,707, 2008 | 52 | 2008 |
Styledrop: Text-to-image generation in any style K Sohn, N Ruiz, K Lee, DC Chin, I Blok, H Chang, J Barber, L Jiang, ... arXiv preprint arXiv:2306.00983, 2023 | 51 | 2023 |
Debiasing vision-language models via biased prompts CY Chuang, V Jampani, Y Li, A Torralba, S Jegelka arXiv preprint arXiv:2302.00070, 2023 | 45 | 2023 |