Saturday, May 06, 2017

Cornell Univ: Powerful Image Morph Technique (SIGGRAPH 2017)

// Visual Attribute Transfer through Deep Image Analogy

Jing Liao, Yuan Yao, Lu Yuan, Gang Hua, Sing Bing Kang
'We propose a new technique for visual attribute transfer across images that may have very different appearance but have perceptually similar semantic structure. By visual attribute transfer, we mean transfer of visual information (such as color, tone, texture, and style) from one image to another. For example, one image could be that of a painting or a sketch while the other is a photo of a real scene, and both depict the same type of scene. Our technique finds semantically-meaningful dense correspondences between two input images. To accomplish this, it adapts the notion of "image analogy" with features extracted from a Deep Convolutional Neutral Network for matching; we call our technique Deep Image Analogy. A coarse-to-fine strategy is used to compute the nearest-neighbor field for generating the results. We validate the effectiveness of our proposed method in a variety of cases, including style/texture transfer, color/style swap, sketch/painting to photo, and time lapse.'

Tuesday, May 02, 2017

The Power of Sound and Sight

Here's a powerful video essay breaking down the important storytelling element of sound and the profound enveloping nature of cinematography in Elem Klimov's film Come and See. Amazing!