Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks

Overview

ForecastingNonverbalSignals

This is the implementation for the paper Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks.

Dependencies

  • python 3.6
  • tensorFlow 1.15
  • numpy
  • pickle5
  • sklearn
  • pandas
  • h5py

Usage

  1. Install virtual environment named SocialActionGAN with dependencies:
conda create -n SocialActionGAN python=3.6 tensorflow=1.15 pickle5 scikit-learn pandas h5py
  1. Download UDIVA_2d.pickle, and put it in the folder dataset. Training model with the default parameters:
(SocialActionGAN): python train.py
  1. Alternatively, download the pre-trained model and put it in the folder model. Forecast the motions, generate the ouput file based on the format of the challenge:
(SocialActionGAN): python generate.py --annotations_dir "/path_to/talk_annotations_test_masked/" --segments_path "/path_to/test_segments_topredict.csv"

Optional

  1. Extract the training data, package it as UDIVA_2d.pickle:
(SocialActionGAN): python preprocessing.py --annotations_dir "/path_to/talk_annotations_train"

License

Apache License 2.0

Citation

If you use this repository for your research, please cite:

@misc{tuyen2021forecasting,
      title={Forecasting Nonverbal Social Signals during Dyadic Interactions with Generative Adversarial Neural Networks}, 
      author={Nguyen Tan Viet Tuyen and Oya Celiktutan},
      year={2021},
      eprint={2110.09378},
      archivePrefix={arXiv},
      primaryClass={cs.AI}
}
Pytorch implementation of SimSiam Architecture

SimSiam-pytorch A simple pytorch implementation of Exploring Simple Siamese Representation Learning which is developed by Facebook AI Research (FAIR)

Saeed Shurrab 1 Oct 20, 2021
Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"

Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng Internati

Princeton Vision & Learning Lab 115 Jan 04, 2023
CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY

M-BERT-Study CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY Motivation Multilingual BERT (M-BERT) has shown surprising cross lingual a

CogComp 1 Feb 28, 2022
Meta-meta-learning with evolution and plasticity

Evolve plastic networks to be able to automatically acquire novel cognitive (meta-learning) tasks

5 Jun 28, 2022
Official Pytorch implementation of RePOSE (ICCV2021)

RePOSE: Iterative Rendering and Refinement for 6D Object Detection (ICCV2021) [Link] Abstract We present RePOSE, a fast iterative refinement method fo

Shun Iwase 68 Nov 15, 2022
ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

ICCV2021 Paper: AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Zongdai 107 Dec 20, 2022
Smart edu-autobooking - Johnson @ DMI-UNICT study room self-booking system

smart_edu-autobooking Sistema di autoprenotazione per l'aula studio [email protected]

Davide Carnemolla 17 Jun 20, 2022
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L

2.1k Jan 02, 2023
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch

Rishikesh (ऋषिकेश) 193 Jan 03, 2023
Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022.

Jadena Official implementation of "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection" in CVPR 2022. arXiv

Qing Guo 13 Nov 29, 2022
OpenMMLab Detection Toolbox and Benchmark

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

OpenMMLab 22.5k Jan 05, 2023
meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

meProp The codes were used for the paper meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (ICML 2017) [pdf]

LancoPKU 107 Nov 18, 2022
Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX.

snc4onnx Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools 1.

Katsuya Hyodo 8 Oct 13, 2022
DeLiGAN - This project is an implementation of the Generative Adversarial Network

This project is an implementation of the Generative Adversarial Network proposed in our CVPR 2017 paper - DeLiGAN : Generative Adversarial Net

Video Analytics Lab -- IISc 110 Sep 13, 2022
MADE (Masked Autoencoder Density Estimation) implementation in PyTorch

pytorch-made This code is an implementation of "Masked AutoEncoder for Density Estimation" by Germain et al., 2015. The core idea is that you can turn

Andrej 498 Dec 30, 2022
Running Google MoveNet Multipose Tracking models on OpenVINO.

MoveNet MultiPose Tracking on OpenVINO

60 Nov 17, 2022
An Implicit Function Theorem (IFT) optimizer for bi-level optimizations

iftopt An Implicit Function Theorem (IFT) optimizer for bi-level optimizations. Requirements Python 3.7+ PyTorch 1.x Installation $ pip install git+ht

The Money Shredder Lab 2 Dec 02, 2021
Implementation of OpenAI paper with Simple Noise Scale on Fastai V2

README Implementation of OpenAI paper "An Empirical Model of Large-Batch Training" for Fastai V2. The code is based on the batch size finder implement

13 Dec 10, 2021
A small library for creating and manipulating custom JAX Pytree classes

Treeo A small library for creating and manipulating custom JAX Pytree classes Light-weight: has no dependencies other than jax. Compatible: Treeo Tree

Cristian Garcia 58 Nov 23, 2022
RealFormer-Pytorch Implementation of RealFormer using pytorch

RealFormer-Pytorch Implementation of RealFormer using pytorch. Includes comparison with classical Transformer on image classification task (ViT) wrt C

Simo Ryu 90 Dec 08, 2022