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README.md

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-# fast_blind_video_consistency
+# Learning Blind Video Temporal Consistency (ECCV 2018) 
+
+[Wei-Sheng Lai](http://graduatestudents.ucmerced.edu/wlai24/), 
+[Jia-Bin Huang](https://filebox.ece.vt.edu/~jbhuang/), 
+[Oliver Wang](http://www.oliverwang.info/), 
+[Eli Shechtman](https://research.adobe.com/person/eli-shechtman/), 
+[Ersin Yumer](http://www.meyumer.com/), 
+and [Ming-Hsuan Yang](http://faculty.ucmerced.edu/mhyang/)
+
+[European Conference on Computer Vision (ECCV), 2018](https://eccv2018.org/)
+
+[[Project page]](http://vllab.ucmerced.edu/wlai24/video_consistency/)[Paper]
+
+<img src="teaser_small.gif" width="1000">
+
+### Table of Contents
+1. [Introduction](#introduction)
+1. [Citation](#citation)
+1. [Requirements and Dependencies](#requirements-and-dependencies)
+1. [Installation](#installation)
+1. [Dataset](#dataset)
+1. [Apply Pre-trained Models](#apply-pre-trained-models)
+1. [Training and Testing](#training-and-testing)
+1. [Image processing algorithms](#image-processing-algorithms)
+
+### Introduction
+Our method takes the original unprocessed and per-frame processed videos as inputs to produce a temporally consistent video. Our approach is agnostic to specific image processing algorithms applied on the original video.
+
+
+
+
+### Citation
+
+If you find the code and datasets useful in your research, please cite:
+
+    @inproceedings{Lai-ECCV-2018,
+        author    = {Lai, Wei-Sheng and Huang, Jia-Bin and Wang, Oliver and Shechtman, Eli and Yumer, Ersin and Yang, Ming-Hsuan}, 
+        title     = {Learning Blind Video Temporal Consistency}, 
+        booktitle = {European Conference on Computer Vision},
+        year      = {2018}
+    }
+
+
+### Requirements and dependencies
+- [Pytorch 0.4](https://pytorch.org/)
+- [TensorboardX](https://github.com/lanpa/tensorboardX)
+- [LPIPS](https://github.com/richzhang/PerceptualSimilarity) (for evaluation)
+
+
+### Dataset
+
+
+### Installation
+Download repository:
+
+    $ git clone https://github.com/phoenix104104/fast_blind_video_consistency.git
+
+
+### Apply pre-trained models
+
+
+### Training and testing
+
+### Image processing algorithms
+We use the following algorithms to obtain per-frame processed results:
+
+**Style transfer**
+