TAPe+ML: A Compact Structured Representation for Multi-Task Computer Vision
Rethinking vision systems through structural perceptual representation to enhance multi-task learning efficiency.
We present TAPe+ML v3, a compact computer vision system based on TAPe (Theory of Active Perception), a structured representation that encodes relations among perceptual elements before recognition. Instead of operating directly on pixel tensors, the system uses a shared TAPe repr...
ArXiv CS.CV
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Moving beyond raw pixel processing toward structured representational frameworks marks a significant shift in how AI models interpret complex visual environments. By encoding relational hierarchies before recognition, this architecture achieves higher efficiency and adaptability for multi-task computer vision applications.
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