Parallel and High-Fidelity Text-to-Lip Generation; AAAI 2022 ; Official code

Related tags

Deep Learningpytorchaaai2022
Overview

Parallel and High-Fidelity Text-to-Lip Generation

arXiv GitHub Stars downloads

This repository is the official PyTorch implementation of our AAAI-2022 paper, in which we propose ParaLip (for text-based talking face synthesis) .

Video Demos

P+22M_si1076.mp4

Video samples can be found in our demo page.

🚀 News:

  • Feb.24, 2022: Our new work, NeuralSVB was accepted by ACL-2022 arXiv. Project Page.
  • Dec.01, 2021: ParaLip was accepted by AAAI-2022.
  • July.14, 2021: We submitted ParaLip to Arxiv arXiv.

Environments

conda create -n your_env_name python=3.7
source activate your_env_name 
pip install -r requirements.txt

ParaLip

1. Preparation

Data Preparation

We provide the first frame of each test example for inference. Besides, we include the audio pieces of 5 test examples to generate talking lip videos with human voice.

a) Download and decompress the TCD-TIMIT dataset, then put them in the data directory

tar -xvf timit.tar
mv timit data/

b) Run the following scripts to pack the dataset for inference.

export PYTHONPATH=.
python datasets/lipgen/timit/gen_timit.py --config configs/lipgen/timit/lipgen_timit.yaml

We don't provide the full datasets of TCD-TIMIT because of the licence issue. You can download it by yourself if necessary.

2. Inference Example

CUDA_VISIBLE_DEVICES=0 python tasks/timit_lipgen_task.py --config configs/lipgen/timit/lipgen_timit.yaml --exp_name timit_2 --infer --reset

We also provide:

  • the pre-trained model of ParaLip on TCD-TIMIT. Remember to put the pre-trained models in checkpoints/timit_2 directory respectively.

Citation

@misc{https://doi.org/10.48550/arxiv.2107.06831,
  doi = {10.48550/ARXIV.2107.06831},
  
  url = {https://arxiv.org/abs/2107.06831},
  
  author = {Liu, Jinglin and Zhu, Zhiying and Ren, Yi and Huang, Wencan and Huai, Baoxing and Yuan, Nicholas and Zhao, Zhou},
  
  keywords = {Multimedia (cs.MM), Computer Vision and Pattern Recognition (cs.CV), FOS: Computer and information sciences, FOS: Computer and information sciences},
  
  title = {Parallel and High-Fidelity Text-to-Lip Generation},
  
  publisher = {arXiv},
  
  year = {2021},
  
  copyright = {arXiv.org perpetual, non-exclusive license}
}
You might also like...
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis

HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p

Rishikesh (à€‹à€·à€żà€•à„‡à€¶) 31 Dec 8, 2022
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

Facebook Research 75 Dec 19, 2022
《Towards High Fidelity Face Relighting with Realistic Shadows》(CVPR 2021)
《Towards High Fidelity Face Relighting with Realistic Shadows》(CVPR 2021)

Towards High Fidelity Face-Relighting with Realistic Shadows Andrew Hou, Ze Zhang, Michel Sarkis, Ning Bi, Yiying Tong, Xiaoming Liu. In CVPR, 2021. T

null 114 Dec 10, 2022
Tensorflow python implementation of
Tensorflow python implementation of "Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos"

Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos This repository is the official tensorflow python implementation

Yasamin Jafarian 287 Jan 6, 2023
A two-stage U-Net for high-fidelity denoising of historical recordings
A two-stage U-Net for high-fidelity denoising of historical recordings

A two-stage U-Net for high-fidelity denoising of historical recordings Official repository of the paper (not submitted yet): E. Moliner and V. VÀlimÀk

Eloi Moliner Juanpere 57 Jan 5, 2023
Implementation for HFGI: High-Fidelity GAN Inversion for Image Attribute Editing
Implementation for HFGI: High-Fidelity GAN Inversion for Image Attribute Editing

HFGI: High-Fidelity GAN Inversion for Image Attribute Editing High-Fidelity GAN Inversion for Image Attribute Editing Update: We released the inferenc

Tengfei Wang 371 Dec 30, 2022
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis
SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis

SCI-AIDE : High-fidelity Few-shot Histopathology Image Synthesis for Rare Cancer Diagnosis Pretrained Models In this work, we created synthetic tissue

Emirhan KurtuluƟ 1 Feb 7, 2022
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text ClassiïŹcation》(AAAI 2021) GitHub:

LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text ClassiïŹcation

null 76 Dec 5, 2022
Official implementation for paper Knowledge Bridging for Empathetic Dialogue Generation (AAAI 2021).
Official implementation for paper Knowledge Bridging for Empathetic Dialogue Generation (AAAI 2021).

Knowledge Bridging for Empathetic Dialogue Generation This is the official implementation for paper Knowledge Bridging for Empathetic Dialogue Generat

Qintong Li 50 Dec 20, 2022
Comments
  • How to create the *_PHN.txt for specific sentences?

    How to create the *_PHN.txt for specific sentences?

    Hi, I want the mouth to say sentences I specify, so I need to make phoneme files like *_PHN.txt in the timit directory. I would like to ask if there is any tool to do this?

    opened by a312863063 1
  • How to train ParaLip?

    How to train ParaLip?

    I have already tested through the pretrained model, but i still cannot to train it. I think the code lack the trainning code. Is it available to share in the repository? Thank you!

    opened by Zeqing-Wang 2
Owner
Zhying
Incoming student of [email protected]
Zhying
GitHub Repository
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.

============================================================================================================ `MILA will stop developing Theano https:

9.6k Dec 31, 2022
Official Pytorch Implementation of Length-Adaptive Transformer (ACL 2021)

Length-Adaptive Transformer This is the official Pytorch implementation of Length-Adaptive Transformer. For detailed information about the method, ple

Clova AI Research 93 Dec 28, 2022
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.

MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data

Chengxi Zang 6 Jan 02, 2023
Official Implementation of VAT

Semantic correspondence Few-shot segmentation Cost Aggregation Is All You Need for Few-Shot Segmentation For more information, check out project [Proj

Hamacojr 114 Dec 27, 2022
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

3k Jan 08, 2023
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models

Finding an Unsupervised Image Segmenter in each of your Deep Generative Models Description Recent research has shown that numerous human-interpretable

Luke Melas-Kyriazi 61 Oct 17, 2022
Gym-TORCS is the reinforcement learning (RL) environment in TORCS domain with OpenAI-gym-like interface.

Gym-TORCS Gym-TORCS is the reinforcement learning (RL) environment in TORCS domain with OpenAI-gym-like interface. TORCS is the open-rource realistic

naoto yoshida 400 Dec 27, 2022
Applying PVT to Semantic Segmentation

Applying PVT to Semantic Segmentation Here, we take MMSegmentation v0.13.0 as an example, applying PVTv2 to SemanticFPN. For details see Pyramid Visio

35 Nov 30, 2022
A repository for the paper "Improved Adversarial Systems for 3D Object Generation and Reconstruction".

Improved Adversarial Systems for 3D Object Generation and Reconstruction: This is a repository for the paper "Improved Adversarial Systems for 3D Obje

Edward Smith 188 Dec 25, 2022
A scikit-learn compatible neural network library that wraps PyTorch

A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look

4.9k Dec 31, 2022
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models

tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener

Eunice Jun 11 Nov 15, 2022
A PyTorch implementation of "From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network" (ICCV2021)

From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network The official code of VisionLAN (ICCV2021). VisionLAN successfully a

81 Dec 12, 2022
Awesome Monocular 3D detection

Awesome Monocular 3D detection Paper list of 3D detetction, keep updating! Contents Paper List 2022 2021 2020 2019 2018 2017 2016 KITTI Results Paper

Zhikang Zou 184 Jan 04, 2023
Material for my PyConDE & PyData Berlin 2022 Talk "5 Steps to Speed Up Your Data-Analysis on a Single Core"

5 Steps to Speed Up Your Data-Analysis on a Single Core Material for my talk at the PyConDE & PyData Berlin 2022 Description Your data analysis pipeli

Jonathan Striebel 9 Dec 12, 2022
This library is a location of the LegacyLogger for PyTorch Lightning.

neptune-contrib Documentation See neptune-contrib documentation site Installation Get prerequisites python versions 3.5.6/3.6 are supported Install li

neptune.ai 26 Oct 07, 2021
Large scale PTM - PPI relation extraction

Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT The silver standard

1 Feb 25, 2022
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

Phil Wang 97 Dec 28, 2022
Python implementation of "Single Image Haze Removal Using Dark Channel Prior"

##Dependencies pillow(~2.6.0) Numpy(~1.9.0) If the scripts throw AttributeError: __float__, make sure your pillow has jpeg support e.g. try: $ sudo ap

Joyee Cheung 73 Dec 20, 2022
SAT Project - The first project I had done at General Assembly, performed EDA, data cleaning and created data visualizations

Project 1: Standardized Test Analysis by Adam Klesc Overview This project covers: Basic statistics and probability Many Python programming concepts Pr

Adam Muhammad Klesc 1 Jan 03, 2022
Using multidimensional LSTM neural networks to create a forecast for Bitcoin price

Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co

Jakob Aungiers 318 Dec 14, 2022