Midv-699 May 2026

Pros:

Cons:

We propose MIDV‑699, a unified framework that addresses both challenges: MIDV-699


| Item | Details | |------|---------| | Ticket ID | MIDV‑699 | | Title | [Insert concise title] | | Author / Owner | [Name / team] | | Target Release | [e.g., v2.4.1] | | Type | Feature / Enhancement / Bug‑Fix / Refactor | | Scope | [High‑level description – e.g., “Add support for multi‑currency invoices”] | | Related tickets / dependencies | MIDV‑654, MIDV‑712, external library upgrade | | Date of review | 2026‑04‑11 | Cons: We propose MIDV‑699 , a unified framework


| Category | Positive Observations | |----------|-----------------------| | Code Quality | • Clear, single‑responsibility classes.
• Consistent naming and JavaDoc comments.
• Proper use of Optional to avoid null checks. | | Test Coverage | • High unit‑test coverage (> 90 % for new classes).
• Added integration tests that spin up an in‑memory DB, verifying migration and CRUD flow. | | Performance | • Benchmarks show ≤ 15 ms latency for the main service call (well under the 50 ms SLA). | | Security | • Input validation performed using the existing InputSanitizer.
• No new privileged endpoints exposed. | | Documentation | • All new APIs documented with Swagger annotations.
• User‑facing UI changes reflected in the help guide. | | Backward Compatibility | • Feature is gated behind a config flag, making rollout safe. | | Deployment | • Migration script is idempotent; can be re‑run without side effects. | | Item | Details | |------|---------| | Ticket


  • Licensing: research-only license prohibiting commercial redistribution and requiring proper citation.
  • Retention and takedown: clear procedure for participants to request removal of donated documents.
  • Provide evaluation scripts, reproducible training configs, and Docker containers for easy replication.
  • Document segmentation
  • Field detection + OCR (single-frame)
  • Video-based OCR and tracking
  • Layout analysis / template classification
  • Identity attribute extraction and normalization
  • Presentation-attack detection (PAD)
  • Forgery localization
  • End-to-end pipeline evaluation
  • Evaluation protocols: