5 accepted papers
Visual place recognition(VPR) is a crucial technology for autonomous driving and robotic navigation. However, severe appearance and perspective changes often lead to degradation of algorithm performance. Current methods mainly utilize single-modality RGB images, which are sensitive to environmental…
As a crucial part of mobile robotics and autonomous driving, Visual Place Recognition (VPR) is usually addressed by recognizing its similar reference images from a pre-obtained database. However, VPR always suffers from environmental changes, such as weather, illumination, perceptual-aliasing and so…
Visual place recognition (VPR) is a challenging issue for robotics and autonomous systems, focusing on utilizing visual information for robot localization. Currently, hierarchical architecture is being employed by growing works, which embraces RANSAC-based geometric verification for re-ranking. Howe…
"Knowing merely where the target is located is not sufficient for many real-life scenarios. In contrast, capturing rich details about the tracked target via its semantic trajectory, i.e. who/what this target is interacting with and when, where, and how they are interacting over time, is especially c…
Real-time and robust long-term visual localization is a crucial technology for autonomous driving. Season and illumination variance make this problem more challenging. At present, most of excellent visual localization algorithms cannot run in real-time on devices with limited computing resources. In…