High Quality — Midv-682

Feature Specification – MIDV‑682

8. Quality checks and validation

• Verify annotation consistency (no overlapping identical field labels)
• Check transcription encoding (UTF-8), normalize date formats (ISO 8601)
• Validate bounding boxes inside image bounds
• Sample human review of random subsets for annotation correctness

The production is categorized under several specific themes: MIDV-682

• Provide a sample training pipeline (code outline) for document detection + OCR.
• Suggest model architectures and hyperparameters tuned for mobile deployment.
• Summarize a short literature list of papers using MIDV datasets.

What is MIDV-682?

1. Run a pre‑trained vision model (e.g., MobileNet‑V3 or a distilled CLIP variant) locally in the browser (WebAssembly/TF.js) to generate a list of candidate tags.
2. Apply business‑specific taxonomy filters (e.g., “brand‑approved” vs “restricted”) to surface only relevant tags.
3. Present the suggested tags in an editable UI component, allowing the user to accept, edit, or discard each suggestion.
4. Persist the final tag set to the asset’s metadata in the backend via the existing /assets/:id/tags endpoint.

Stick to Established Databases: Rely on recognized media databases, official studio websites, and legitimate digital retailers. Avoid clicking on unverified search results promising free downloads or streaming. Feature Specification – MIDV‑682 8

• Different lighting conditions
• Rotations and perspective distortions
• Blurs/noise
• Occlusions, folds, and reflections
• Different backgrounds and capture devices