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Affordance Detection
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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.
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3D-AffordanceLLM: Harnessing Large Language Models for Open-Vocabulary Affordance Detection in 3D Worlds
Which objects help me to act effectively? Reasoning about physically-grounded affordances
Multi-label affordance mapping from egocentric vision
Open-Vocabulary Affordance Detection in 3D Point Clouds
Affordance detection with Dynamic-Tree Capsule Networks
Phrase-Based Affordance Detection via Cyclic Bilateral Interaction
Detecting Object States vs Detecting Objects: A New Dataset and a Quantitative Experimental Study
One-Shot Object Affordance Detection in the Wild
One-Shot Affordance Detection
Affordance Transfer Learning for Human-Object Interaction Detection
3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding
Recognizing Object Affordances to Support Scene Reasoning for Manipulation Tasks
Egocentric affordance detection with the one-shot geometry-driven Interaction Tensor
Scene Understanding for Autonomous Manipulation with Deep Learning
What can I do here? Leveraging Deep 3D saliency and geometry for fast and scalable multiple affordance detection
Detect, anticipate and generate: Semi-supervised recurrent latent variable models for human activity modeling
Visual Affordance and Function Understanding: A Survey
AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection
Multi-Modal Trip Hazard Affordance Detection On Construction Sites
What can you do with a rock? Affordance extraction via word embeddings
Detecting Affordances by Visuomotor Simulation
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