5 accepted papers
With the increased importance of autonomous navigation systems has come an increasing need to protect the safety of Vulnerable Road Users (VRUs) such as pedestrians. Predicting pedestrian intent is one such challenging task, where prior work predicts the binary cross/no-cross intention with a fusion…
The problem of determining geolocation through visual inputs, known as Visual Place Recognition (VPR), has attracted significant attention in recent years owing to its potential applications in autonomous self-driving systems. The rising interest in these applications poses unique challenges, partic…
Unconstrained Asian roads often involve poor infrastructure, affecting overall road safety. Missing traffic signs are a regular part of such roads. Missing or non-existing object detection has been studied for locating missing curbs and estimating reasonable regions for pedestrians on road scene ima
Object detection plays an essential role in providing localization, path planning, and decision making capabilities in autonomous navigation systems. However, existing object detection models are trained and tested on a fixed number of known classes. This setting makes the object detection model dif…
"High-quality structured data with rich annotations are critical components in intelligent vehicle systems dealing with road scenes. However, data curation and annotation require intensive investments and yield low-diversity scenarios. The recently growing interest in synthetic data raises questions…