The paper "CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization" by Shuang Guo and Guillermo Gallego addresses the problem of rotational motion estimation using event cameras, which are bio-inspired visual sensors that capture pixel-wise intensity changes and output asynchronous event streams. The authors conduct a systematic study to evaluate and compare previous methods under unified criteria and propose a novel event-based rotation-only bundle adjustment (BA) approach. This approach leverages the state-of-the-art Contrast Maximization (CMax) framework, which avoids the need to convert events into frames. The proposed BA is used to build CMax-SLAM, an event-based rotation-only SLAM system comprising a front-end and a back-end. The front-end estimates the angular velocity of the camera, while the back-end refines the continuous-time trajectory of the camera using the BA. The effectiveness of the proposed method is demonstrated through comprehensive experiments on synthetic and real-world datasets, including indoor, outdoor, and space scenarios. The authors also discuss the challenges of evaluating rotation-only methods on non-strictly rotational data and propose a proxy for reprojection error as a figure of merit. The source code and novel data sequences are released to benefit the community.The paper "CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization" by Shuang Guo and Guillermo Gallego addresses the problem of rotational motion estimation using event cameras, which are bio-inspired visual sensors that capture pixel-wise intensity changes and output asynchronous event streams. The authors conduct a systematic study to evaluate and compare previous methods under unified criteria and propose a novel event-based rotation-only bundle adjustment (BA) approach. This approach leverages the state-of-the-art Contrast Maximization (CMax) framework, which avoids the need to convert events into frames. The proposed BA is used to build CMax-SLAM, an event-based rotation-only SLAM system comprising a front-end and a back-end. The front-end estimates the angular velocity of the camera, while the back-end refines the continuous-time trajectory of the camera using the BA. The effectiveness of the proposed method is demonstrated through comprehensive experiments on synthetic and real-world datasets, including indoor, outdoor, and space scenarios. The authors also discuss the challenges of evaluating rotation-only methods on non-strictly rotational data and propose a proxy for reprojection error as a figure of merit. The source code and novel data sequences are released to benefit the community.