TAPe+ML: A Compact Structured Representation for Multi-Task Computer Vision
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 representation and a modular recognition architecture for image classification, object detection, and instance segmentation. TAPe+ML v3 combines background and contour processing, local object localization, prototype-based classification, and a coordinator for specialized submodels. Across the reported experiments, it uses fewer than 100,000 parameters. On COCO object detection, it obtains 84.7 mAP50 and 65.3 mAP50-95...
| Authors | Sergey Kurinov, Alexey Upatov |
|---|---|
| Primary category | cs.CV |
| Published | 15 September 2026 |
| Last updated at source | 24 September 2026 |
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