The MIDV-2020 dataset was created by the Smart Engines team to address the challenges of capturing identity documents in unconstrained mobile environments. Unlike static scans, these videos include real-world "noise" like motion blur, varying lighting, and background interference. The Purpose of MIDV-226

: Detecting "replay attacks" where a screen is recorded instead of a physical document.

: It serves as a benchmark for Optical Character Recognition (OCR) systems.

: Handling the reflective surfaces typical of laminated ID cards or plastic driver's licenses.

: The video captures how different angles and distances affect data extraction accuracy.

: Training lightweight AI models that can run directly on a phone without needing a powerful server.

: Improving how banks verify identities through mobile apps.