You can use this to process mesh data, generate 3D faces from morphable model, reconstruct 3D face with a single image and key points as inputs, render faces with difference lightings (for more, please see examples).

Oct 19, 2024 · Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019)

Mar 3, 2021 · First, you need'll some face topology that establishes semantic relationship between 3D positions of the face mesh vertices and some 2D texture coordinates. I'd start with the canonical face model used in MediaPipe Face Geometry module (UV visualization; Face Geometry formats: metadata schema, mesh 3D schema, metadata text).

''' Generate 2d uv maps representing different attributes (colors, depth, image position, etc) : render attributes to uv space. ''' import os, sys import numpy as np import scipy.io as sio from skimage import io import skimage.transform from time import time import matplotlib.pyplot as plt sys.path.append ('..') import face3d from face3d import ...

Jul 19, 2018 · This is an official python implementation of PRN. PRN is a method to jointly regress dense alignment and 3D face shape in an end-to-end manner. More examples on Multi-PIE and 300VW can be seen in YouTube . The main features are:

Aug 12, 2023 · This repository contains reimplementation of existing neural renderer based 2D-to-3D mesh editing and texture mapping approach using the latest libraries like Pytorch etc.

Create 3D models (.obj, .glb, etc.) from terrain maps using a python script in Blender. Interact with the models through the web or mobile using Google Poly A library of HiRISE 3D models can …

FFHQ-UV is a large-scale facial UV-texture dataset that contains over 50,000 high-quality texture UV-maps with even illuminations, neutral expressions, and cleaned facial regions, which are desired characteristics for rendering realistic 3D face models under different lighting conditions.

Python tools for 3D face: 3DMM, Mesh processing (transform, camera, light, render), 3D face representations. - face3d/examples/5_render.py at master · yfeng95/face3d

This project uses a pre-trained depth estimation model to convert 2D images into 3D models. It leverages a pre-trained model from the Hugging Face Transformers library, and generates a 3D mesh based on the predicted depth map.