Context Aware Image

Context-aware image processing focuses on leveraging surrounding information to improve image manipulation tasks. Current research emphasizes incorporating contextual information from various sources, including neighboring pixels, semantic scene graphs, and even external data like navigation maps, often using transformer-based architectures and convolutional neural networks for feature extraction and fusion. This field is crucial for advancing applications like autonomous driving (improving scene understanding and object detection), image inpainting and retargeting (generating realistic and coherent image completions), and web navigation (enhancing agent decision-making). The development of more efficient and robust context-aware models is driving progress across multiple computer vision domains.