Global Image Feature

Global image features represent a high-level summary of an image's content, aiming to capture overall scene characteristics rather than fine-grained details. Current research focuses on integrating global features with local features, often using hybrid architectures like CNN-Transformer networks or incorporating attention mechanisms to selectively emphasize relevant regions within an image. This approach improves performance in various applications, including object recognition, image classification, and human pose estimation, by providing a more comprehensive and robust representation of visual information than relying solely on global or local features.