<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Kai Tang | RCL Group</title><link>https://rcl-group.github.io/authors/kai-tang/</link><atom:link href="https://rcl-group.github.io/authors/kai-tang/index.xml" rel="self" type="application/rss+xml"/><description>Kai Tang</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 09 Jul 2025 00:00:00 +0000</lastBuildDate><image><url>https://rcl-group.github.io/media/icon_hu_c9b5ec8305c0ee34.png</url><title>Kai Tang</title><link>https://rcl-group.github.io/authors/kai-tang/</link></image><item><title>Gaussian-LIC2 Released on arXiv</title><link>https://rcl-group.github.io/blog/2025-gaussian-lic2/</link><pubDate>Wed, 09 Jul 2025 00:00:00 +0000</pubDate><guid>https://rcl-group.github.io/blog/2025-gaussian-lic2/</guid><description>&lt;p&gt;Our latest work
is now available on
! This paper presents the first photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geometric accuracy, and real-time performance. By employing a lightweight zero-shot depth model to generate dense depth maps from sparse LiDAR measurements and RGB cues, our system enables reliable Gaussian initialization in LiDAR-blind areas and significantly improves applicability for sparse LiDAR sensors. We also demonstrate improved pose estimation under LiDAR degradation scenarios via tightly incorporating photometric constraints from the Gaussian map into the continuous-time factor graph optimization. Code and dataset will be publicly available.&lt;/p&gt;</description></item><item><title>Gaussian-LIC2: LiDAR-Inertial-Camera Gaussian Splatting SLAM</title><link>https://rcl-group.github.io/publications/gaussian-lic2-2025/</link><pubDate>Tue, 01 Jul 2025 00:00:00 +0000</pubDate><guid>https://rcl-group.github.io/publications/gaussian-lic2-2025/</guid><description/></item><item><title>Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline</title><link>https://rcl-group.github.io/publications/coco-lic-2023/</link><pubDate>Fri, 01 Sep 2023 00:00:00 +0000</pubDate><guid>https://rcl-group.github.io/publications/coco-lic-2023/</guid><description/></item></channel></rss>