DUSt3R (Dense and Unconstrained Stereo 3D Reconstruction) introduces a novel paradigm in multi-view 3D reconstruction, eliminating the need for predefined camera poses and intrinsics. 3D ...
Object Insertion in Gaussian Splatting: Paper Explanation and Training of MCMC in Gsplat
3D Gaussian splatting (3DGS) has recently gained recognition as a groundbreaking approach in radiance fields and computer graphics. It stands out as a jack of all trades, addressing challenges that ...
Depth Pro: The Sharp Monocular Depth Estimation from Apple Research
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 ...
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 even a ...
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 year. A groundbreaking paper in ...
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 ...
