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Found 3 papers, 1 papers with code
Face Recognition Using Synthetic Face Data
In the field of deep learning applied to face recognition, securing large-scale, high-quality datasets is vital for attaining precise and reliable results.
Knowing the Distance: Understanding the Gap Between Synthetic and Real Data For Face Parsing
Our study highlights the importance of content diversity in synthetic datasets and challenges the notion that the photorealism gap is the most critical factor affecting the performance of computer vision models trained on synthetic data.
Why You Should Try the Real Data for the Scene Text Recognition
In this paper we also introduce a text recognition model.
Ranked #1 on
Scene Text Recognition
on ICDAR 2003
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