RGB D Datasets

RGB-D datasets, comprising synchronized RGB images and depth maps, are crucial for advancing 3D computer vision. Current research focuses on creating larger, more diverse datasets encompassing various object categories, scenes (including challenging real-world conditions like occlusion), and applications like robotic grasping and agricultural automation. This involves developing novel model architectures, such as transformers and dual-path networks, to effectively integrate RGB and depth information for tasks including object pose estimation, instance re-identification, and shape completion. The availability of high-quality RGB-D datasets and associated benchmarks is driving significant progress in 3D scene understanding and enabling the development of more robust and practical applications in robotics, augmented reality, and beyond.