Ashish Patel 🇮🇳’s Post

𝗗𝗮𝘆-𝟮𝟳𝟵 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗙𝗮𝗸𝗲 𝗜𝘁 𝗧𝗶𝗹𝗹 𝗬𝗼𝘂 𝗠𝗮𝗸𝗲 𝗜𝘁: Face analysis in the wild using synthetic data alone by Microsoft Follow me for a similar post: 🇮🇳 Ashish Patel Interesting Facts : 🔸 This paper is published ICCV2021 with 2 citations. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/ezqvwk6W Dataset: https://lnkd.in/en-K-NWa ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone. The community has long enjoyed the benefits of synthesizing training data with graphics, but the domain gap between real and synthetic data has remained a problem, especially for human faces.  🔸 Researchers have tried to bridge this gap with data mixing, domain adaptation, and domain-adversarial training, but we show that it is possible to synthesize data with minimal domain gap, so that models trained on synthetic data generalize to real in-the-wild datasets.  🔸 We describe how to combine a procedurally-generated parametric 3D face model with a comprehensive library of hand-crafted assets to render training images with unprecedented realism and diversity. We train machine learning systems for face-related tasks such as landmark localization and face parsing, showing that synthetic data can both match real data in accuracy as well as open up new approaches where manual labelling would be impossible. #computervision #artificialintelligence #innovation