Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Related tags

Deep Learning computer-vision deep-learning structure-from-motion landmark-detection unsupervised-learning 3d-face-reconstruction
Overview

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment

This repository shows two tasks: Face landmark detection and Face 3D reconstruction, which is described in this paper: Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

Installation

  1. Clone the repository.
  2. install dependencies.
pip install -r requirement.txt

Face landmark detection

Running a pre-trained model

  1. Download landmark pre-trained model at GoogleDrive, and put it into FaceLandmark/model/
  2. Run the test file
python Facial_landmark.py

Face 3D reconstruction

Running a pre-trained model

  1. Download face 3D reconstruction pre-trained model at GoogleDrive, and put it into FaceReconstruction/checkpoints/

  2. Run the inference.py file to generate disparity map

python inference.py --dataset-dir './FaceReconstruction/test_image/' --output-dir './FaceReconstruction/output/' --pretrained './FaceReconstruction/checkpoints/dispnet_model_best.pth.tar' --resnet-layers 18 --output-disp
  1. Run the generate_ply.py file to generate point cloud .ply file
python generate_ply.py
You might also like...
Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV
Realtime Face Anti Spoofing with Face Detector based on Deep Learning using Tensorflow/Keras and OpenCV

Realtime Face Anti-Spoofing Detection 🤖 Realtime Face Anti Spoofing Detection with Face Detector to detect real and fake faces Please star this repo

Prem Kumar 86 Aug 3, 2022
"MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction" (CVPRW 2022) & (Winner of NTIRE 2022 Challenge on Spectral Reconstruction from RGB)

MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction (CVPRW 2022) Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Z

Yuanhao Cai 274 Jan 5, 2023
PyTorch implementation of the paper: Long-tail Learning via Logit Adjustment

logit-adj-pytorch PyTorch implementation of the paper: Long-tail Learning via Logit Adjustment This code implements the paper: Long-tail Learning via

Chamuditha Jayanga 53 Dec 23, 2022
This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization This codebase is the official implementation of Test-Time Classifier A

null 47 Dec 28, 2022
Forecasting for knowable future events using Bayesian informative priors (forecasting with judgmental-adjustment).
Forecasting for knowable future events using Bayesian informative priors (forecasting with judgmental-adjustment).

What is judgyprophet? judgyprophet is a Bayesian forecasting algorithm based on Prophet, that enables forecasting while using information known by the

AstraZeneca 56 Oct 26, 2022
BARF: Bundle-Adjusting Neural Radiance Fields 🤮 (ICCV 2021 oral)

BARF 🤮 : Bundle-Adjusting Neural Radiance Fields Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey IEEE International Conference on Comp

Chen-Hsuan Lin 539 Dec 28, 2022
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale

XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf

Microsoft 125 Jan 4, 2023
Fashion Landmark Estimation with HRNet
Fashion Landmark Estimation with HRNet

HRNet for Fashion Landmark Estimation (Modified from deep-high-resolution-net.pytorch) Introduction This code applies the HRNet (Deep High-Resolution

SVIP Lab 91 Dec 26, 2022
[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.
[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.

LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequ

SVIP Lab 45 Dec 12, 2022
Comments
  • Landmarks problem

    Landmarks problem

    Hello, I have tried the landmark detection on my images (just replaced the references in the code Facial_landmak.py and they do not appear to detect any significant features of the face and they do not match between the images. The images are png squared 384x384 as yours used in test_landmark folder. What am I doing wrong? landmarks_1 landmarks_2

    opened by baba-yaga 0
Owner
BoomStar
Computer Vision
BoomStar
GitHub
ONNX-PackNet-SfM: Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX

Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX

Ibai Gorordo 14 Dec 9, 2022
Square Root Bundle Adjustment for Large-Scale Reconstruction

RootBA: Square Root Bundle Adjustment Project Page | Paper | Poster | Video | Code Table of Contents Citation Dependencies Installing dependencies on

Nikolaus Demmel 205 Dec 20, 2022
Rotation-Only Bundle Adjustment

ROBA: Rotation-Only Bundle Adjustment Paper, Video, Poster, Presentation, Supplementary Material In this repository, we provide the implementation of

Seong 51 Nov 29, 2022
Poplar implementation of "Bundle Adjustment on a Graph Processor" (CVPR 2020)

Poplar Implementation of Bundle Adjustment using Gaussian Belief Propagation on Graphcore's IPU Implementation of CVPR 2020 paper: Bundle Adjustment o

Joe Ortiz 34 Dec 5, 2022
A face dataset generator with out-of-focus blur detection and dynamic interval adjustment.

A face dataset generator with out-of-focus blur detection and dynamic interval adjustment.

Yutian Liu 2 Jan 29, 2022
Code for BMVC2021 "MOS: A Low Latency and Lightweight Framework for Face Detection, Landmark Localization, and Head Pose Estimation"

MOS-Multi-Task-Face-Detect Introduction This repo is the official implementation of "MOS: A Low Latency and Lightweight Framework for Face Detection,

null 104 Dec 8, 2022
End-to-end face detection, cropping, norm estimation, and landmark detection in a single onnx model

onnx-facial-lmk-detector End-to-end face detection, cropping, norm estimation, and landmark detection in a single onnx model, model.onnx. Demo You can

atksh 42 Dec 30, 2022
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python

Multimedia Computing Group, Nanjing University 99 Dec 30, 2022
A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.

ManhattanSLAM Authors: Raza Yunus, Yanyan Li and Federico Tombari ManhattanSLAM is a real-time SLAM library for RGB-D cameras that computes the camera

null 117 Dec 28, 2022
Web service for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation based on OpenFace 2.0

OpenGaze: Web Service for OpenFace Facial Behaviour Analysis Toolkit Overview OpenFace is a fantastic tool intended for computer vision and machine le

Sayom Shakib 4 Nov 3, 2022