Python 3
Pytorch1.0.0
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
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Dynamic Object Detection
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Background Prediction
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Background Inpainting following Generative Inpainting
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Dynamic Object Motion Prediction
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Video Inpainting modified from Deep-Flow-Guided-Video-Inpainting
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
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
We use LPIPS for evaluation
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}
}
If you have any question, please feel free to contact me (Yue Wu, ywudg@connect.ust.hk)
The code is developed based on Vid2Vid https://github.com/NVIDIA/vid2vid