NeuralGIF

Code for Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing(ICCV21)

We present Neural Generalized Implicit Functions (Neural-GIF), to animate people in clothing as a function of body pose. Neural-GIF learns directly from scans, models complex clothing and produces pose-dependent details for realistic animation. We show for four different characters the query input pose on the left (illustrated with a skeleton) and our output animation on the right.

Dataset and Pretrained models

https://nextcloud.mpi-klsb.mpg.de/index.php/s/FweAP5Js58Q9tsq

Installation

1. Install kaolin: https://github.com/NVIDIAGameWorks/kaolin

2. conda env create -f neuralgif.yml

3. conda activate neuralgif

Training NeuralGIF

 1. Edit configs/*yaml with correct path
        a. data/data_dir:
        b. data/split_file: <path to train/test split file> (see example in dataset folder)
        c. experiment/root_dir: training dir
        d. experiment/exp_name: <exp_name>
 2 . python trainer_shape.py --config=<path to config file>

Generating meshes from NeuralGIF

1. python generator.py --config=<path to config file>

Data preparation

1. SMPL pose and shape parameters:  https://github.com/bharat-b7/IPNet

2. Save the registartion data and original scan data as: 
    
    a. data_dir/scan_dir: contain original scans
    b. data_dir/beta.npy: SMPL beta parameter of subject
    c. data_dir/pose.npz: SMPL pose parameters for all frames of scan

3. Prepare training data:
    python prepare_data/clothseq_data.py -data_dir=<path to data directory>

Visualisation

python visualisation/render_meshes.py -mesh_path=<folder containing meshes> -out_dir=<output dir>

Citation:

@inproceedings{tiwari21neuralgif,
  title = {Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing},
  author = {Tiwari, Garvita and Sarafianos, Nikolaos and Tung, Tony and Pons-Moll, Gerard},
  booktitle = {International Conference on Computer Vision ({ICCV})},
  month = {October},
  year = {2021},
  }