Aug 27, 2024 · Here are 10 public repositories matching this topic... Official repo for DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image (CVPR 2022). Implementation of a 3D Face Generative Model. SeIF: Semantic-constrained Deep Implicit Function for Single-image 3D Head Reconstruction.

Official repo for DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image (CVPR 2022). Topics

Mar 7, 2022 · Let’s take a look, how to build 3D models from points, edges and primitives in python. How to perform elementary 3D modeling techniques: move, rotate, merge, subtract and others.

Jul 9, 2024 · This article is a simple introduction to creating a 3D modeling and animation app using Python, PyQt, and PyOpenGL. We started by setting up a basic PyQt application window and then integrated OpenGL for rendering 3D graphics.

May 23, 2023 · FLAME is a lightweight and expressive generic head model learned from over 33,000 of accurately aligned 3D scans. FLAME combines a linear identity shape space (trained from head scans of 3800 subjects) with an articulated neck, jaw, and eyeballs, pose-dependent corrective blendshapes, and additional global expression blendshapes.

MetaHead-F provides precise and view-consistent 3D control over the shape and appearance of heads in a highly decoupled manner, including challenging expressions and illumination. In comparison, previous models could only output or control moderate expressions. It can also generate heads in a 3D-aware stylization manner.

Jul 20, 2023 · Using material from this library will allow you to work with visualizing a 3D model of a person and its measurements. Among the available options are measuring body lengths and circumferences....

Apr 9, 2025 · EMOCA takes a single image of a face as input and produces a 3D reconstruction. EMOCA sets the new standard on reconstructing highly emotional images in-the-wild. A 3DMM fitting framework using Pytorch. Official repo for DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image (CVPR 2022).

This project implements some basic functions related to 3D faces. 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).

We propose CLIP-Head, a novel approach towards text-driven neural parametric 3D head model generation. Our method takes simple text prompts in natural language, describing the appearance & facial expressions, and generates 3D neural head avatars with accurate geometry and high-quality texture maps.