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In the field of deep learning applied to face recognition, securing large-scale, high-quality datasets is vital for attaining precise and reliable results. However, amassing significant volumes of high-quality real data faces hurdles such as time lim
Externí odkaz:
http://arxiv.org/abs/2305.10079
Autor:
Friedman, Eli, Lehr, Assaf, Gruzdev, Alexey, Loginov, Vladimir, Kogan, Max, Rubin, Moran, Zvitia, Orly
The use of synthetic data for training computer vision algorithms has become increasingly popular due to its cost-effectiveness, scalability, and ability to provide accurate multi-modality labels. Although recent studies have demonstrated impressive
Externí odkaz:
http://arxiv.org/abs/2303.15219
Over the past few years there has been major progress in the field of synthetic data generation using simulation based techniques. These methods use high-end graphics engines and physics-based ray-tracing rendering in order to represent the world in
Externí odkaz:
http://arxiv.org/abs/2206.00148
Akademický článek
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Publikováno v:
Proceedings of SPIE; Nov2008, Issue 1, p69142G-69142G-9, 9p
