Image Scaling

Image scaling, the process of resizing images, is crucial in computer vision, impacting tasks from object detection to image quality assessment. Current research focuses on developing efficient scaling methods for resource-constrained devices (e.g., using in-sensor compression and selective regions of interest) and improving the performance of lightweight models like Vision Transformers, even with minimally scaled images. A significant challenge lies in mitigating vulnerabilities to image-scaling attacks, which can manipulate predictions in machine learning systems. These advancements are vital for optimizing performance in various applications, from edge computing to improving the robustness and reliability of image processing pipelines.