EgoMaize: A First-Person Maize Instance Segmentation Benchmark under Severe Field Occlusion
Close-range first-person field images are important for mobile maize phenotyping because many plant-level traits depend on in-canopy structures that are difficult to ob serve from overhead views. However, post-seedling maize fields create a difficult in stance segmentation setting: stems, leaves, tassels, and neighboring plants are elon gated, repetitive, and strongly occluded. We introduce EgoMaize, a compact benchmark for first-person maize instance segmentation, where the task is to predict ownership consistent plant masks and plant-owned stem/tassel cues from close-range field images with severe same-class overlap. Existing visible-only labels can fragment one physi cal plant into dis...
| Authors | Jiayi Li, Zihan Zhang, Erhankang Yan et al. |
|---|---|
| Primary category | cs.CV |
| Published | 11 September 2026 |
| Last updated at source | 11 September 2026 |
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