FEW-SHOT KNOWLEDGE TRANSFER FOR FINE-GRAINED CARTOON FACE GENERATION

Paper

This repository provides the official Pytorch implementation of our paper: FEW-SHOT KNOWLEDGE TRANSFER FOR FINE-GRAINED CARTOON FACE GENERATION (ICME 21 oral ).

Requirements

• python == 3.6
• tensorflow == 2.2.0
• tensorflow_gpu==1.14.0
• torch==1.4.0
• torchvision==0.5.0
• face_alignment==1.0.0

Pre-trained model

We released the pre-trained single model and multi-group model so that people could test more widely. Please download the pre-trained models from [Google Driver]

Dataset

Please download the dataset from [Google Driver] and extract it to dataset folder.

Usage

Train

We train our model on a server with a NVIDIA Tesla V100 of 32G memory.

python train.py 

• If the memory of gpu is not sufficient, set --light to True
  • But it may not perform well
  • paper version is --light to False

Test

python test.py --dataset {folder_for_dataset} --model_path {path_to_model_ckpt} --remark {exp_name} --label {0, 1, 2, 3 for specific groups}

Architecture

Results

Reference

Our codes refer to Project Photo2cartoon