ANONYMIZED CASE STUDY
Automotive Panel and Damage Annotation
An anonymized multi-task workflow for vehicle components, damage detection and detailed damage geometry.
Project context
Vehicle inspection data required different annotation treatments for panels, visible damage and detailed defect regions. Client identity and source imagery remain confidential.
Annotation challenge
Subtle scratches, reflections, dirt and damage crossing component boundaries required consistent interpretation. The appropriate geometry also changed by task, from detection boxes to detailed polygons or masks.
Data and task
- Vehicle exterior, top and lower-view imagery
- Panel and component classes
- Damage, scratch and rim-related regions
Workflow
- Mapped panel and damage taxonomies
- Applied bounding boxes for detection tasks
- Used polygons or segmentation where boundary detail was required
- Incorporated review feedback into subsequent batches
Important edge cases
- Reflections that resemble damage
- Faint or low-contrast scratches
- Damage spanning more than one panel
- Cropped, dirty or poorly lit components
Quality assurance
- Panel and damage-class checks
- False-positive reflection review
- Geometry and boundary correction
- Batch-level feedback and final export checks
Delivery outputs
- Bounding-box annotations
- Polygon or segmentation outputs where required
- Client-platform or requested export formats
Outcome
The workflow supported multiple vehicle-damage tasks while keeping class definitions, geometry requirements and reviewer corrections aligned with the relevant project guideline.
This case study is intentionally anonymized. No client names, confidential source images or unsupported performance claims are included.