As computer vision algorithms increase in capability, their applications in clinical systems
will become more pervasive. These applications include: diagnostics, such as colonoscopy …

The grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, the grid-centric perception is less prevalent than object-centric perception as …

We present DrivingGaussian an efficient and effective framework for surrounding dynamic
autonomous driving scenes. For complex scenes with moving objects we first sequentially …

This paper aims to tackle the problem of modeling dynamic urban streets for autonomous
driving scenes. Recent methods extend NeRF by incorporating tracked vehicle poses to …

Holistic understanding of urban scenes based on RGB images is a challenging yet important
problem. It encompasses understanding both the geometry and appearance to enable novel …

Abstract Neural Radiance Fields (NeRFs) have shown remarkable success in synthesizing
photorealistic views from multi-view images of static scenes but face challenges in dynamic …

Visual odometry estimates the motion of a moving camera based on visual input. Existing
methods mostly focusing on two-view point tracking often ignore the rich temporal context in …

Neural implicit fields have been a de facto standard in novel view synthesis. Recently there
exist some methods exploring fusing multiple modalities within a single field aiming to share …

The rapid growth of 3D Gaussian Splatting (3DGS) has revolutionized neural rendering,
enabling real-time production of high-quality renderings. However, the previous 3DGS …

Autonomous vehicles rely extensively on perception systems to navigate and interpret their
surroundings. Despite significant advancements in these systems recently, challenges …