SOTAVerified

Affordance Detection

Affordance detection refers to identifying the potential action possibilities of objects in an image, which is an important ability for robot perception and manipulation.

Image source: Object-Based Affordances Detection with Convolutional Neural Networks and Dense Conditional Random Fields

Unlike other visual or physical properties that mainly describe the object alone, affordances indicate functional interactions of object parts with humans.

Papers

Showing 21–23 of 23 papers

TitleStatusHype
Multi-Modal Trip Hazard Affordance Detection On Construction Sites—0
What can you do with a rock? Affordance extraction via word embeddings—0
Detecting Affordances by Visuomotor Simulation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DGCNNAIOU0.18—Unverified
#ModelMetricClaimedVerifiedStatus
1DGCNNAIOU0.14—Unverified
#ModelMetricClaimedVerifiedStatus
1DGCNNAIOU0.13—Unverified
#ModelMetricClaimedVerifiedStatus
1DGCNNAIOU0.16—Unverified