Visual Encoding

Visual encoding focuses on representing visual information in a format suitable for machine processing, primarily for tasks involving multimodal understanding (combining images and text). Current research emphasizes efficient and robust encoding methods, particularly within large language models, often employing techniques like early fusion of visual and textual data, hierarchical aggregation of diverse visual features, and the use of multiple vision encoders to capture broader contextual information. These advancements are improving the performance of vision-language models across various applications, including image captioning, object tracking, and question answering, while also addressing challenges like handling high-resolution images and limited training data.