Image Semantic

Image semantic compression aims to reduce image data size while preserving essential semantic information, rather than focusing solely on pixel-perfect reconstruction. Current research emphasizes leveraging large multimodal models and deep learning architectures, such as transformers and generative adversarial networks, to encode and decode images based on their semantic content, often incorporating techniques like attention mechanisms and hierarchical representations. This approach promises significant improvements in data efficiency for storage and transmission, particularly at ultra-low bitrates, and enhances the performance of downstream AI tasks that rely on compressed image data.