Frame Based

Frame-based vision, relying on traditional cameras capturing discrete images, is being augmented by event-based vision, which uses cameras that asynchronously record changes in light intensity. Current research focuses on effectively fusing data from these two modalities, employing techniques like Gaussian splatting for efficient representation and hierarchical feature refinement networks for improved object detection and motion estimation. This cross-modal approach aims to overcome limitations of each individual system, leading to more robust and efficient computer vision applications, particularly in challenging conditions like low light or high speed motion, with implications for autonomous driving and robotics.