Hi there, thank you for your kind attention of our work 

"Deep Video-Based Performance Synthesis from Sparse Multi-View Capture".

This github page contains all the code and data used in our paper (including the code for all comparisons).

We will give a detailed introduction of the folder's directory structure as follows.

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Folder's directory structure

                     Folder Name             Function
	     
1. dataset      ---  1_Synthetic             This folder contains the download link of the synthetic data used in our paper

                ---  2_Real                  This folder contains the download link of the real data used in our paper
	 	  
2. comparisons  ---  Zhu_CVPR2018            This folder contains the code of the paper [Zhu et al. CVPR2018]
 
                ---  Zeng_ECCV2018           This folder contains the code of the paper [Zeng et al. ECCV2018]
					
	        ---  Sitzmann_CVPR2019       This folder contains the code of the paper [Sitzmann et al. CVPR2019]
					
3. ours                                      This folder contains the code of our method


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[Zhu et al. CVPR2018]: Zhu, Hao, et al. View extrapolation of human body from a single image. CVPR. 2018.

[Zeng et al. ECCV2018]: Huang Z, Li T, Chen W, et al. Deep volumetric video from very sparse multi-view performance capture. ECCV. 2018.

[Sitzmann et al. ECCV2018]: Sitzmann, Vincent, et al. Deepvoxels: Learning persistent 3d feature embeddings. CVPR. 2019.

In each directory, there has a text "ReadMe.txt", we have detailed

                                     the environment condiguration,
															 
			             the download link of the dataset, 
															 
			             the functional description of the code,
															 
			             and the code usage steps.

If you have any questions, please don't hesitate to contact us. ^_^

You can open an issue through the button "Issues" on the github.

Thank you for your kind attention again.