RGB Modality

RGB modality, representing visual data in red, green, and blue channels, is a cornerstone of computer vision, with current research focusing on improving its robustness and effectiveness in various applications. This involves developing novel architectures that leverage complementary modalities like depth or thermal data for enhanced performance, particularly in challenging conditions such as low light or noisy environments, often employing attention mechanisms and cross-modal fusion techniques. These advancements are crucial for improving the accuracy and reliability of applications ranging from robotic manipulation and semantic segmentation to salient object detection and person re-identification, ultimately leading to more robust and versatile computer vision systems.