Event Stream Super Resolution

Event stream super-resolution (ESR) aims to enhance the low spatial and temporal resolution of data from event cameras, which capture asynchronous brightness changes rather than full frames. Recent research focuses on developing novel neural network architectures, such as those employing recursive multi-branch fusion or bilateral event mining, to effectively process the unique characteristics of event streams and improve super-resolution accuracy and efficiency. These advancements are significant for improving the performance of event-based vision systems in applications like object recognition and video reconstruction, where high-resolution data is crucial.