Dense Feature

Dense features, high-dimensional representations capturing rich spatial information within images or point clouds, are central to many computer vision and related tasks. Current research focuses on improving the extraction, selection, and utilization of these features, employing techniques like vision transformers, diffusion models, and graph attention networks within various architectures designed for tasks such as segmentation, object pose estimation, and place recognition. This work aims to enhance accuracy, efficiency, and robustness in these applications, particularly in challenging scenarios like dense crowds or occluded scenes. The resulting advancements have significant implications for diverse fields, including medical image analysis, robotics, and autonomous driving.