Dense 3D Reconstruction

Dense 3D reconstruction aims to create complete, detailed 3D models from 2D images or other sensor data, a crucial task in robotics, computer vision, and medical imaging. Current research emphasizes real-time performance and accuracy using various approaches, including neural networks (e.g., transformers, neural radiance fields), multi-view stereo techniques, and fusion of data from multiple sensors (e.g., cameras, LiDAR, event cameras). These advancements are driving improvements in applications ranging from autonomous navigation and augmented reality to minimally invasive surgery and robotic manipulation.