PSP-HDRI$+$: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models
Abstract
We introduce a new synthetic data generator PSP-HDRI$+$ that proves to be a superior pre-training alternative to ImageNet and other large-scale synthetic data counterparts. We demonstrate that pre-training with our synthetic data will yield a more general model that performs better than alternatives even when tested on out-of-distribution (OOD) sets. Furthermore, using ablation studies guided by person keypoint estimation metrics with an off-the-shelf model architecture, we show how to manipulate our synthetic data generator to further improve model performance.
Cite
Text
Ebadi et al. "PSP-HDRI$+$: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models." ICML 2022 Workshops: Pre-Training, 2022.Markdown
[Ebadi et al. "PSP-HDRI$+$: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models." ICML 2022 Workshops: Pre-Training, 2022.](https://mlanthology.org/icmlw/2022/ebadi2022icmlw-psphdri/)BibTeX
@inproceedings{ebadi2022icmlw-psphdri,
title = {{PSP-HDRI$+$: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models}},
author = {Ebadi, Salehe Erfanian and Dhakad, Saurav and Vishwakarma, Sanjay and Wang, Chunpu and Jhang, You-Cyuan and Chociej, Maciek and Crespi, Adam and Thaman, Alex and Ganguly, Sujoy},
booktitle = {ICML 2022 Workshops: Pre-Training},
year = {2022},
url = {https://mlanthology.org/icmlw/2022/ebadi2022icmlw-psphdri/}
}