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2023 Low-Power Computer Vision Challenge (LPCVC) Summary

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arxiv 2403.07153 v1 pith:4CXG4LI7 submitted 2024-03-11 cs.CV

classification cs.CV
keywords lpcvcaccuracyvisionchallengecomputerarticlecompetitionexecution
verification ladder T0 review T1 audit T2 compute T3 formal
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This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of computer vision (CV) on edge devices. Most CV researchers focus on improving accuracy, at the expense of ever-growing sizes of machine models. LPCVC balances accuracy with resource requirements. Winners must achieve high accuracy with short execution time when their CV solutions run on an embedded device, such as Raspberry PI or Nvidia Jetson Nano. The vision problem for 2023 LPCVC is segmentation of images acquired by Unmanned Aerial Vehicles (UAVs, also called drones) after disasters. The 2023 LPCVC attracted 60 international teams that submitted 676 solutions during the submission window of one month. This article explains the setup of the competition and highlights the winners' methods that improve accuracy and shorten execution time.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge

    cs.CV 2026-04 conditional novelty 3.0 of 10

    A competition report covering 2025 LPCVC's Qualcomm AI Hub evaluation system and the winning solutions in classification, open-vocabulary segmentation, and depth estimation.

  2. Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge

    cs.CV 2026-04 unverdicted novelty 2.0 of 10

    The 2025 LPCVC winners demonstrate practical techniques for low-power image classification under varied conditions, open-vocabulary segmentation from text prompts, and monocular depth estimation.

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