Dec 11, 2018 · How to efficiently train a Deep Learning model to construct 3D object from one single RGB image.

This Python script reconstructs 3D models from 2D images. It uses a pre-trained deep learning model for depth estimation and Open3D for 3D processing, generating a point cloud and a 3D …

This proposes an end-to-end deep learning method for digitizing highly detailed clothed humans that can infer both 3D surface and texture from a single image, and optionally, multiple input …

Feb 28, 2020 · To bring this new visual format to more people, we have used state-of-the-art machine learning techniques to produce 3D photos from virtually any standard 2D picture.

This repository presents Deep3D, a robust deep learning framework designed to transform 2D images into realistic 3D representations. Built using PyTorch, the project leverages state-of-the …

Nov 1, 2024 · We show a good strategy for transforming 2D visual input into 3D representations that employ PyTorch3D for complex mesh manipulation and rendering, as well as a Python …

Researchers deploy convolutional networks for the reconstruction of 3D images. This paper compares the existing techniques and proposes a MeshCNN-based nove1 technique to …

Feb 19, 2025 · Deep learning techniques help AI 3D model creators analyze the depth, texture, and structure of a picture, allowing them to reconstruct the 3D equivalent with unbelievable …

In this work, we have chosen to aim to: Implement an application to transform 2D images into 3D images based mainly on Deep learning and Convolutional Neural Networks (CNN). For this, …

Aug 15, 2023 · In this paper, several depth image-based rendering (DIBR) approaches using state-of-the-art single-frame depth generation neural networks and inpaint algorithms are …