Keywords: Machine Learning, Synthetic Data, Computer Vision, Human-Centric Computer Vision, ImageNet, Pre-training
TL;DR: A synthetic dataset generator for human-centric computer vision whose data is a better pre-training alternative to ImageNet and other synthetic dataset counterparts.
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.
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