Lune

NeurIPS2024顶会

LiT: Unifying LiDAR "Languages" with LiDAR Translator

Yixing Lao, Tao Tang, Xiaoyang Wu, Peng Chen, Kaicheng Yu, Hengshuang Zhao

2024年份
3被引次数
1顶会引用

摘要

LiDAR data exhibits significant domain gaps due to variations in sensors, vehicles, and driving environments, creating “language barriers” that limit the effective use of data across domains and the scalability of LiDAR perception models. To address these challenges, we introduce the LiDAR Translator (LiT) , a framework that directly translates LiDAR data across domains, enabling both cross-domain adaptation and multi-domain joint learning. LiT integrates three key components: a scene modeling module for precise foreground and background reconstruction, a LiDAR modeling module that models LiDAR rays statistically and simulates ray-drop

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper1

问问它们各自怎么用它

它引用的顶会 Paper33

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖