Application · Trajectory matching
Wearable ImageNet: Synthesizing Tileable Textures via Dataset Distillation
George Cazenavette, Tongzhou Wang, Antonio Torralba, Alexei A. Efros, Jun-Yan Zhu
CVPR 2022 Workshop · first public 2022-01-01
In one paragraph
Generates tileable distilled "textures" by sampling random crops from a toroidal canvas of trajectory-matching-distilled pixels while enforcing that every crop is itself effective distilled training data for its class, producing infinite repeating patterns that visually summarize an ImageNet category and are suitable for printing on fabric or clothing.
Where it sits
- Trajectory matching (Surrogate matching)
- Setting: Image classification
BibTeX (generated; prefer the venue's official entry)
@article{cazenavette2022wearable,
title = {Wearable ImageNet: Synthesizing Tileable Textures via Dataset Distillation},
author = {George Cazenavette and Tongzhou Wang and Antonio Torralba and Alexei A. Efros and Jun-Yan Zhu},
journal = {CVPR 2022 Workshop},
year = {2022}
}Nearby in Trajectory matching
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