3 accepted papers
Significant advances in robotics and machine learning have resulted in many datasets designed to support research into autonomous vehicle technology. However, these datasets are rarely suitable for a wide variety of navigation tasks. For example, datasets that include multiple cameras often have sho…
"Modern pre-trained architectures struggle to retain previous information while undergoing continuous fine-tuning on new tasks. Despite notable progress in continual classification, systems designed for complex vision tasks such as detection or segmentation still struggle to attain satisfactory perf…
The ability to produce large-scale maps for nav-igation, path planning and other tasks is a crucial step for autonomous agents, but has always been challenging. In this work, we introduce BEV-SLAM, a novel type of graph-based SLAM that aligns semantically-segmented Bird's Eye View (BEV) predictions…