EvSLAM: A Benchmark Framework for Event-Camera SLAM in High-Speed Maneuvers

The authors propose EvSLAM, a benchmark framework for event-camera state estimation that covers multiple data-collection platforms, extreme lighting, and challenging motion patterns, and provides an explicit definition of high-speed maneuvers along with new evaluation metrics. The paper first analyzes the limitations of existing event-camera VO/VIO methods and the shortcomings of public datasets, then uses the framework to evaluate current state-of-the-art methods, summarizing better architectures and problems that remain to be solved.