Event Based Video Frame Interpolation

Event-based video frame interpolation (E-VFI) aims to generate smooth, high-frame-rate videos from sparsely sampled event camera data and conventional video frames. Current research focuses on improving the accuracy of motion estimation using techniques like edge-guided attention mechanisms and anisotropic optical flow adjustments, often within recurrent neural network or transformer-based architectures. These advancements address limitations in handling motion blur, occlusion, and rolling shutter artifacts, leading to higher-quality interpolated videos. The resulting improvements in video quality and efficiency have significant implications for applications requiring high temporal resolution, such as robotics, autonomous driving, and high-speed video analysis.