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  • PIoU Loss: Towards Accurate Oriented Object Detection in Complex . . .
    Therefore, a novel loss, Pixels-IoU (PIoU) Loss, is formulated to exploit both the angle and IoU for accurate OBB regression The PIoU loss is derived from IoU metric with a pixel-wise form, which is simple and suitable for both horizontal and oriented bounding box
  • Piou - YouTube
    Welcome to the Piou's adventure ! ⚠ Things to know about 🐣ᴾᶦᵒᵘ * 🐣ᴾᶦᵒᵘ is french, so try be nice with his english spelling please ! * 🐣ᴾᶦᵒᵘ has an ol
  • piou - definition, thesaurus and related words from WordNet-Online
    WordNet-Online dictionary Definition, thesaurus and related words for 'piou' Synonyms, antonyms, hypernyms, hyponyms, meronyms, usage examples, and much more
  • PIoU Loss: Towards Accurate Oriented Object Detection in Complex . . .
    To demonstrate its effectiveness, we evaluate the PIoU loss on both anchor-based and anchor-free frameworks The experimental results show that PIoU loss can dramatically improve the performance of OBB detectors, particularly on objects with high aspect ratios and complex backgrounds
  • piou · PyPI
    Piou includes an optional interactive TUI (Text User Interface) mode powered by Textual This provides a rich terminal experience with command suggestions, history, and inline completions
  • mani9441 PPYOLOE-with-PIoU-Loss - GitHub
    This project introduces a Perceptual IoU (PIoU) loss—a corner-aware extension of IoU that enforces perceptual boundary consistency When integrated into PP-YOLOE, PIoU aims to improve localization stability for occluded targets
  • InterpIoU: Rethinking Bounding Box Regression with Interpolation-Based . . .
    PIoU Powerful IoU (PIoU) [21] is a recent addition to the IoU-based loss family, designed to be lighter yet more efficient compared to SIoU PIoU introduces a target-adaptive penalty that guides regression along a more direct and effective path
  • PIoU Loss: Towards Accurate Oriented Object Detection in Complex . . . - ECVA
    Therefore, a novel loss, Pixels-IoU (PIoU) Loss, is formulated to exploit both the angle and IoU for accurate OBB regression The PIoU loss is derived from IoU metric with a pixel-wise form, which is simple and suitable for both horizontal and oriented bounding box





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