Depth Pro, is an foundational zero shot metric depth estimation model from Apple ML, nails at creating high resolution, sharp monocular metric depth maps in less than a second. Depth Pro achieves SOTA ...
Training 3D U-Net for Brain Tumor Segmentation Challenge – Medical Imaging
3D U-Net, a powerful deep learning architecture for medical image segmentation, is designed to process 3D volumetric data like brain tumors, enabling a more comprehensive and precise analysis of brain ...
CVPR 2024 Key Research & Dataset Papers – Part 2
CVPR 2024 (Computer Vision and Pattern Recognition) is an annual conference held from June 17th to 21st at the Seattle Convention Center, USA, which was a huge success. The IEEE CVPR 2024 Research ...
Depth Anything: Accelerating Monocular Depth Perception
Depth Anything represents a groundbreaking advancement in the field of monocular depth perception. This research article outlines the innovative approach taken in designing the Depth Anything model, ...
3D LiDAR Visualization using Open3D: A Case Study on 2D KITTI Depth Frames for Autonomous Driving
3D LiDAR sensor (or) 3-dimensional Light Detection and Ranging is an advanced light-emitting instrument that has the ability to perceive the real-world in a 3-dimensional space, just as we humans do. ...
Disparity Estimation Using Deep Learning
A conventional video or picture captures the three-dimensional world in two dimensions, losing crucial information regarding depth, which many applications now demand. Depth estimation is a ...