Mind the Gaps: A Curated Benchmark for Form Field Detection
Form Field Detection (FFD) is a fundamental component of document understanding systems, enabling applications ranging from large-scale industrial digitization to accessible form interaction for automated analysis. Unlike conventional object detection tasks, FFD is inherently challenging because fields are often defined by layout structure and whitespace rather than visible foreground content. Existing large-scale datasets frequently rely on heuristic annotation pipelines, resulting in noisy and inconsistent labels that hinder reliable evaluation. In this work, we introduce mini-CommonForms, a carefully curated FFD benchmark with consistent, high-quality annotations, and present a detaile...
| Authors | Iheb Brini, Omar Moured, Hamza Gbada et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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