June 7, 2024, 4:43 a.m. | Masum Hasan, Cengiz Ozel, Nina Long, Alexander Martin, Samuel Potter, Tariq Adnan, Sangwu Lee, Amir Zadeh, Ehsan Hoque

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.03599v1 Announce Type: cross
Abstract: We propose a new large synthetic hand pose estimation dataset, Hi5, and a novel inexpensive method for collecting high-quality synthetic data that requires no human annotation or validation. Leveraging recent advancements in computer graphics, high-fidelity 3D hand models with diverse genders and skin colors, and dynamic environments and camera movements, our data synthesis pipeline allows precise control over data diversity and representation, ensuring robust and fair model training. We generate a dataset with 583,000 images …

abstract annotation arxiv colors computer computer graphics cs.cv cs.gr cs.lg data dataset diverse dynamic fidelity graphics human novel quality synthetic synthetic data type validation

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