Bilateral Motion

Bilateral motion estimation, focusing on the analysis and prediction of motion from two directions (forward and backward in time), is a key area of research in video processing and computer vision. Current efforts concentrate on improving the accuracy and efficiency of bilateral motion estimation using techniques like transformers and recurrent neural networks, often integrated within larger frameworks for tasks such as video interpolation, compression, and gait recognition. These advancements lead to improved video quality, reduced computational costs, and enhanced capabilities in applications ranging from high-resolution video generation to human activity analysis.