深度模糊 - 标签 - Zhaoylee's Blogs https://zhaoylee.github.io/Blogs_lovelt/tags/%E6%B7%B1%E5%BA%A6%E6%A8%A1%E7%B3%8A/ 深度模糊 - 标签 - Zhaoylee's Blogs Hugo -- gohugo.iozh-CNTue, 24 Mar 2026 10:48:33 +0800 OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection https://zhaoylee.github.io/Blogs_lovelt/posts/obmo-one-bounding-box-multiple-objects-for-monocular-3d-object-detection/ Tue, 24 Mar 2026 10:48:33 +0800 zhaoylee https://zhaoylee.github.io/Blogs_lovelt/posts/obmo-one-bounding-box-multiple-objects-for-monocular-3d-object-detection/ 简述:一个框对应多个物体位置，通过施加软标签，帮助网络训练稳定，从而提升一定的性能;]]> OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection https://zhaoylee.github.io/Blogs_lovelt/posts/obmo--one-bounding-box-multiple-objects-for-monocular-3d-object-detection/ Sun, 15 Mar 2026 21:59:12 +0800 zhaoylee https://zhaoylee.github.io/Blogs_lovelt/posts/obmo--one-bounding-box-multiple-objects-for-monocular-3d-object-detection/

🏛️ 会议/期刊：IEEE TIP
📅 发表年份：2023
💻 开源代码：mrsempress/OBMO_patchnet
📄 论文题目：OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection

这篇发表于 IEEE TIP (2023) 的经典论文 《OBMO: One Bounding Box Multiple Objects for Monocular 3D Object Detection》 切入点非常犀利。它没有在复杂的网络主干上做文章，而是直击单目 3D 目标检测在“底层数学物理逻辑”上的痛点，提出了一种极其优雅的“即插即用（Plug-and-play）”训练策略。

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