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Video Frame Interpolation via Adaptive Separable Convolution
TLDR
This paper develops a deep fully convolutional neural network that takes two input frames and estimates pairs of 1D kernels for all pixels simultaneously, which allows for the incorporation of perceptual loss to train the neural network to produce visually pleasing frames. Expand
Leveraging stereopsis for saliency analysis
TLDR
This paper explores stereopsis for saliency analysis and presents two approaches to stereo saliency detection from stereoscopic images, one based on the global disparity contrast in the input image and one that leverages domain knowledge in stereoscopic photography. Expand
Content-preserving warps for 3D video stabilization
TLDR
A technique that transforms a video from a hand-held video camera so that it appears as if it were taken with a directed camera motion, and develops algorithms that can effectively recreate dynamic scenes from a single source video. Expand
Subspace video stabilization
TLDR
This article focuses on the problem of transforming a set of input 2D motion trajectories so that they are both smooth and resemble visually plausible views of the imaged scene, and offers the first method that both achieves high-quality video stabilization and is practical enough for consumer applications. Expand
Video Frame Interpolation via Adaptive Convolution
TLDR
This paper presents a robust video frame interpolation method that considers pixel synthesis for the interpolated frame as local convolution over two input frames and employs a deep fully convolutional neural network to estimate a spatially-adaptive convolution kernel for each pixel. Expand
Composition-Preserving Deep Photo Aesthetics Assessment
TLDR
This paper presents a composition-preserving deep Con-vNet method that directly learns aesthetics features from the original input images without any image transformations, and adds an adaptive spatial pooling layer upon the regular convolution and pooling layers to directly handle input images with original sizes and aspect ratios. Expand
Multi-View Video Summarization
TLDR
A spatio-temporal shot graph is constructed and the summarization problem is formulated as a graph labeling task, which encodes the correlations with different attributes among multi-view video shots in hyperedges and generates a result based on shot importance evaluated using a Gaussian entropy fusion scheme. Expand
Automatic image retargeting with fisheye-view warping
TLDR
This paper presents a method for adapting large images, such as those taken with a digital camera, for a small display,such as a cellular telephone that uses a non-linear fisheye-view warp that emphasizes parts of an image while shrinking others. Expand
Video retargeting: automating pan and scan
TLDR
A framework that measures the preservation of the source material, and methods for estimating the important information in the video are defined, and results of adapting a variety of source videos to small display sizes are demonstrated. Expand
Image Retargeting Using Mesh Parametrization
TLDR
This paper associates image saliency into the image mesh and regard image structure as constraints for mesh parametrization to emphasize salient objects and minimize visual distortion in image retargeting. Expand
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