Dense Depth Map

Dense depth map estimation aims to generate complete, pixel-level depth information from sparse sensor data or single images, crucial for applications like robotics and autonomous driving. Current research focuses on improving accuracy and efficiency through various approaches, including transformer-based architectures, optimization-guided neural iterations, and multi-modal fusion techniques that leverage RGB images and LiDAR data. These advancements are driving progress in 3D scene understanding, enabling more robust and reliable perception capabilities for a wide range of applications.