Video Regression

Video regression focuses on predicting continuous values from video data, addressing tasks like micro-expression analysis, video reconstruction, and 6D object pose estimation. Recent research emphasizes improving model architectures, such as developing multilayer neural representations (NeRV) to enhance spatial and temporal consistency and employing self-supervised learning to bridge domain gaps in training data. These advancements aim to improve accuracy and efficiency in various applications, including human-computer interaction, video processing, and robotics. The field is actively exploring synergistic approaches that combine different tasks (e.g., spotting and recognition in micro-expression analysis) to achieve superior performance.