Official implementation of Paper "Future Video Synthesis With Object Motion Prediction"(CVPR 2020)

Enviroment

Python 3

Pytorch1.0.0

Components

There are exists several components in our framework. This repo only contain modified files for Generative Inpainting and Deep-Flow-Guided-Video-Inpainting.

We use PWCNet to compute optical flow. Please put the code under './*/models/' directory

• Dynamic Object Detection

• Background Prediction

• Background Inpainting following Generative Inpainting

• Dynamic Object Motion Prediction

• Video Inpainting modified from Deep-Flow-Guided-Video-Inpainting

Data preparation

This document illustrates how the data preprocessing is done. I release the test result in next section. If you want the preprocessed test dataset to verify the result, please drop me an email.

data
├── Cityscapes
│   ├── depth
│   ├── dynamic
│   ├── for_val_data
│   ├── instance_upsnet
│   │   └── origin_data
│   │   └── val
│   ├── leftImg8bit_sequence_512p (Citysapes images in 512x1024)
│   │   └── val
│   │   │     └── frankfurt
│   │   │     └── lindau
│   │   │     └── munster
│   ├── non_rigid_mask
│   ├── semantic 
│   ├── small_object_mask
├── Kitti
│   ├── depth
│   ├── dynamic
│   ├── for_val_data
│   ├── instance_upsnet
│   │   └── origin_data
│   │   └── val
│   ├── raw_data_56p (Kitti images in 256x832)
│   │   └── val
│   │   │    └── 2011_09_26_drive_0060_sync
│   │   │    │    └── image_02
│   │   │    │    │     └── data
│   │   │    └── 2011_09_26_drive_0084_sync
│   │   │    └── 2011_09_26_drive_0093_sync
│   │   │    └── 2011_09_26_drive_0096_sync
│   ├── non_rigid_mask
│   ├── semantic 
│   ├── small_object_mask

Pretrained Models and Results

The test results without intermediate output and pretrained models are in OneDrive

The test results with intermediate output of each test step are in Google Drive

The details of test setting can be found in link

If you want to test the model from beginning, the precise test step is in link

Evaluation

We use LPIPS for evaluation

Citation

If you use our code or paper, please cite:

@InProceedings{Yue_2020_CVPR,
author = {Yue Wu and Rongrong Gao and Jaesik Park and Qifeng Chen},
title = {Future Video Synthesis with Object Motion Prediction},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}

Contact

If you have any question, please feel free to contact me (Yue Wu, [email protected])

Acknowledgement

The code is developed based on Vid2Vid https://github.com/NVIDIA/vid2vid