Summary of Rethinking Score Distillation As a Bridge Between Image Distributions, by David Mcallister et al.
Rethinking Score Distillation as a Bridge Between Image Distributions
by David McAllister, Songwei Ge, Jia-Bin Huang, David W. Jacobs, Alexei A. Efros, Aleksander Holynski, Angjoo Kanazawa
First submitted to arxiv on: 13 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Graphics (cs.GR); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a new approach to understanding the behavior of Score Distillation Sampling (SDS) and its variants by viewing them as solving an optimal-cost transport path from a source distribution to a target distribution. The authors argue that current methods’ characteristic artifacts are caused by linear approximation of the optimal path and poor estimates of the source distribution. They show that calibrating the text conditioning of the source distribution can produce high-quality generation and translation results with little extra overhead, matching or beating the performance of specialized methods. The method is demonstrated in various domains, including text-to-2D, text-based NeRF optimization, translating paintings to real images, optical illusion generation, and 3D sketch-to-real. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper’s new approach helps us understand how Score Distillation Sampling works and why it has some problems. The authors think that these problems come from not accurately estimating the source distribution. They show that if we fix this issue, we can get much better results with just a little extra work. This method is useful in many areas, such as turning text into images, optimizing NeRF for text-based tasks, and creating realistic paintings. |
Keywords
» Artificial intelligence » Distillation » Optimization » Translation
