STRAP: Structured Object Affordance Segmentation with Point Supervision

Understand

With significant annotation savings, point supervision has been proven effective for numerous 2D and 3D scene understanding problems.

• This success is primarily attributed to the structured output space; i.e., samples with high spatial affinity tend to share the same labels.
• Sharing this spirit, we study affordance segmentation with point supervision, wherein the setting inherits an unexplored dual affinity-spatial affinity and label affinity.
• By label affinity, we refer to affordance segmentation as a multi-label prediction problem: A plate can be both holdable and containable.