We introduce Argoverse 2 (AV2)-a collection of three datasets for perception and forecasting
research in the self-driving domain. The annotated Sensor Dataset contains 1,000 …

We introduce the KAIST multi-spectral data set, which covers a great range of drivable
regions, from urban to residential, for autonomous systems. Our data set provides the …

With the advent of commodity autonomous mobiles, it is becoming increasingly prevalent to
recognize under extreme conditions such as night, erratic illumination conditions. This need …

To achieve accurate and robust object detection in the real-world scenario, various forms of
images are incorporated, such as color, thermal, and depth. However, multimodal data often …

We propose VLASE, a framework to use semantic edge features from images to achieve on-
road localization. Semantic edge features denote edge contours that separate pairs of …

For many robotics and intelligent vehicle applications, detection and tracking multiple
objects (DATMO) is one of the most important components. However, most of the DATMO …

To understand the real-world, it is essential to perceive in all-day conditions including cases
which are not suitable for RGB sensors, especially at night. Beyond these limitations, the …

Visual place recognition is a fundamental capability for the localization of mobile robots. It
places image retrieval in the practical context of physical agents operating in a physical …

This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted
to merge visible and infrared images. The objective is to find the best setup independently of …

Disclosed is a stereo camera-based autonomous driving method and apparatus, the method
including estimating a driving situation of a vehicle, determining a parameter to control a …