Image Based Metric

Image-based metrics are quantitative measures assessing the quality and fidelity of images, particularly those generated by AI or derived from other data sources like LiDAR. Current research focuses on developing metrics that better align with human perception, addressing limitations of existing methods like FID and SSIM, particularly for complex scenes and videos. This involves exploring novel architectures, such as transformer-based approaches and statistical modeling of deep features, to capture both global and local image characteristics, as well as temporal aspects in videos. Improved image-based metrics are crucial for evaluating and advancing image generation, scene reconstruction, and anomaly detection technologies.