Affordance Detection

Affordance Detection refers to the identification of potential actions that can be performed on objects in an image. This capability is crucial for robotic perception and manipulation. Unlike merely describing the visual or physical attributes of an object, Affordance Detection emphasizes the functional interactions between parts of the object and humans. By employing techniques such as Convolutional Neural Networks (CNNs) and Dense Conditional Random Fields (DCRFs), the goal of this task is to enhance a robot's understanding and adaptability to its environment, thereby achieving more efficient and safer human-robot collaboration.