3D Computer Vision

3D Gaussian Splatting Introduction – Paper Explanation & Training on Custom Datasets with NeRF Studio Gsplats

3D Gaussian Splatting 3DGS is redefining the landscape of 3D computer graphics and vision but here s a twist it achieves groundbreaking results without relying on any neural networks not

3D Computer Graphics, 3D Computer Vision, 3D Reconstruction, Robotics, SLAM

The Annotated NeRF – Training on Custom Dataset from Scratch in Pytorch

In recent years the field of 3D from multi view has become one of the most popular topics in computer vision conferences with a high number of submitted papers each

3D Computer Graphics, 3D Computer Vision, 3D Reconstruction, Deep Learning, PyTorch, Robotics, SLAM

Training 3D U-Net for Brain Tumor Segmentation Challenge – Medical Imaging

This articles discussed Training 3D U Net for Brain Tumor Segmentation BraTS2023 Glioma Detection It touches upon the importance of 3D U Net over 2D U Net for MRI Brain

3D Computer Vision, Computer Vision, Deep Learning, Medical Imaging

Sapiens: Foundation for Human Vision Models by Meta

The article primarily discusses capabilities Sapiens a foundational human vision model by meta achieves state of the art performance in tasks like 2D pose estimation body part segmentation normal and

3D Computer Vision, Computer Vision, Deep Learning, Generative AI, SpatialAI-Depth

Introduction to LiDAR SLAM: LOAM and LeGO-LOAM Paper and Code Explanation with ROS 2 Implementation

LiDAR SLAM is a crucial component in robotics perception widely used in both industry and academia for its efficiency and robustness in localization and mapping In robotics perception research LiDAR

3D Computer Vision, Robotics, ROS, SLAM

CVPR 2024: An Overview and Key Papers

CVPR 2024 showcased groundbreaking AI and computer vision research highlighting generative image dynamics advanced 3D modeling and innovative video editing techniques OpenCV featured prominently presenting OpenCV5 and collaborating with leading

3D Computer Vision, Computer Vision, Deep Learning, Diffusion Models, Generative AI