From 88fa820f32e7d6ce0351c2d85ea9144294993ea7 Mon Sep 17 00:00:00 2001 From: Cameron Date: Tue, 25 Oct 2016 16:34:55 -0600 Subject: Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c2e051d..3ebfb19 100644 --- a/README.md +++ b/README.md @@ -155,7 +155,7 @@ Animations can be rendered by applying the algorithm to each source frame. For

### Gradient Descent Initialization -The gradient descent is controlled using `--init_img_type` for single images and `--init_frame_type` or `--init_first_frame_type` for video frames. For a single image, the gradient descent can be initialized with white noise `random`, the content image `content`, or the style image `style`. For video frames, the gradient descent can also be initialized with the previous stylized frame `prev` or the previous stylized frame warped to the current frame `prev_warp`. White noise allows an arbitrary number of distinct images to be generated. Whereas, initializing with a fixed image converges to the same output. +The initialization of the gradient descent is controlled using `--init_img_type` for single images and `--init_frame_type` or `--init_first_frame_type` for video frames. For single images, the gradient descent can be initialized with white noise `random`, the content image `content`, or the style image `style`. For video frames, the gradient descent can also be initialized with the previous stylized frame `prev` or the previous stylized frame warped to the current frame `prev_warp`. White noise allows an arbitrary number of distinct images to be generated. Whereas, initializing with a fixed image converges to the same output. Here we reproduce Figure 6 from the first paper:

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