Video super-resolution aims to restore low-resolution videos into their high-resolution counterparts. Existing methods typically rely on optical flow, which assumes linear motion and is sensitive to rapid lighting changes, to capture inter-frame information. Event cameras can asynchronously output high temporal resolution event streams, which can reflect nonlinear motion and are robust to lighting changes. Inspired by these characteristics, we propose an Event-driven Bidirectional Video Super-Resolution (EBVSR) framework. Firstly, we propose an event-assisted temporal alignment module that utilizes events to generate nonlinear motion to align adjacent frames, complementing flow-based methods. Secondly, we build an event-based frame synthesis module that enhances the network’s robustness to lighting changes through a bidirectional cross-modal fusion design. Experimental results on synthetic and real …
本文提出一种事件驱动的双向视频超分辨率框架（EBVSR），利用事件相机的高时间分辨率特性捕捉非线性运动，并设计事件辅助的时间对齐模块，以补充光流法在快速光照变化下的不足。同时构建基于事件的帧合成模块，通过双向跨模态融合增强网络对光照变化的鲁棒性。在合成和真实数据上的实验验证了该方法在视频超分辨率任务中的有效性。