Name
Abstract | ||
|---|---|---|
We introduce a new dataset of 293,008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists. Each item is photographed from a variety of angles. We provide baseline results on 1) high-resolution image generation, and 2) image generation conditioned on the given text descriptions. We invite the community to improve upon these baselines. In this paper, we also outline the details of a challenge that we are launching based upon this dataset. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Machine Learning | Image generation,High definition,Baseline (configuration management),Artificial intelligence,Natural language processing,Pixel,Generative grammar,Mathematics,Machine learning |
DocType | Volume | Citations |
Journal | abs/1806.08317 | 5 |
PageRank | References | Authors |
0.38 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Negar Rostamzadeh | 1 | 33 | 6.22 |
| Seyedarian Hosseini | 2 | 5 | 0.71 |
| Thomas Boquet | 3 | 8 | 1.07 |
| Wojciech Stokowiec | 4 | 6 | 1.06 |
| Ying Zhang | 5 | 47 | 2.89 |
| Christian Jauvin | 6 | 9 | 1.96 |
| Chris Pal | 7 | 2140 | 106.53 |