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Self-Explainable Affordance Learning with Embodied Caption
In the field of visual affordance learning, previous methods mainly used abundant images or videos that delineate human behavior patterns to identify action possibility regions for object manipulation, with a variety of applications in robotic tasks.
One for All: One-stage Referring Expression Comprehension with Dynamic Reasoning
However, one unsolved issue of these models is that the number of reasoning steps needs to be pre-defined and fixed before inference, ignoring the varying complexity of expressions.
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