解析2025低功耗视觉挑战赛冠军方案，揭示边缘设备高效模型设计趋势。
Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge
- 采用高通AIHub平台实现跨设备一致可复现的评测框架
- 三赛道冠军方案在光照、文本提示和单目深度任务中均突破性能瓶颈
- 为未来视觉竞赛设计提供可复用的评估与激励机制参考
IEEE低功耗计算机视觉挑战赛（LPCVC）旨在推动适用于边缘设备的高效视觉模型发展，在准确率与延迟、内存容量、能耗等约束间取得平衡。2025年挑战赛包含三个赛道：(1) 多种光照条件与风格下的图像分类，(2) 文本提示的开放词汇分割，(3) 单目深度估计。本文介绍了LPCVC 2025的设计，包括竞赛结构与评估框架，该框架集成高通AI Hub以实现一致且可复现的基准测试。文章还展示了各赛道优胜方案，并总结关键趋势与观察。最后，提出对未来计算机视觉竞赛的改进建议。
原文摘要 · Abstract (English)
The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy with constraints such as latency, memory capacity, and energy use. The 2025 challenge featured three tracks: (1) Image classification under various lighting conditions and styles, (2) Open-Vocabulary Segmentation with Text Prompt, and (3) Monocular Depth Estimation. This paper presents the design of LPCVC 2025, including its competition structure and evaluation framework, which integrates the Qualcomm AI Hub for consistent and reproducible benchmarking. The paper also introduces the top-performing solutions from each track and outlines key trends and observations. The paper concludes with suggestions for future computer vision competitions.
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