Egocentric RGB

Egocentric RGB research focuses on understanding and interpreting visual data captured from a first-person perspective, primarily using RGB cameras mounted on head-mounted devices. Current research heavily utilizes transformer-based architectures to address challenges like self-occlusion and complex scene dynamics, tackling tasks such as 3D pose estimation (human and object), action recognition, and collision prediction. This field is significant for advancing human-computer interaction, robotics, and virtual/augmented reality applications by enabling more natural and intuitive interactions with technology and environments. Large-scale datasets with rich annotations are being developed to facilitate further progress.