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Locality-constrained Linear Coding for image classification
TLDR
This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM, using the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation.
Image Super-Resolution Via Sparse Representation
TLDR
This paper presents a new approach to single-image superresolution, based upon sparse signal representation, which generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods.
Generative Image Inpainting with Contextual Attention
TLDR
This work proposes a new deep generative model-based approach which can not only synthesize novel image structures but also explicitly utilize surrounding image features as references during network training to make better predictions.
Interactive Facial Feature Localization
TLDR
An improvement to the Active Shape Model is proposed that allows for greater independence among the facial components and improves on the appearance fitting step by introducing a Viterbi optimization process that operates along the facial contours.
Free-Form Image Inpainting With Gated Convolution
TLDR
The proposed gated convolution solves the issue of vanilla convolution that treats all input pixels as valid ones, generalizes partial convolution by providing a learnable dynamic feature selection mechanism for each channel at each spatial location across all layers.
Relevance feedback: a power tool for interactive content-based image retrieval
TLDR
A relevance feedback based interactive retrieval approach that effectively takes into account the subjectivity of human perception of visual content and the gap between high-level concepts and low-level features in CBIR.
Image super-resolution as sparse representation of raw image patches
TLDR
It is shown that a small set of randomly chosen raw patches from training images of similar statistical nature to the input image generally serve as a good dictionary, in the sense that the computed representation is sparse and the recovered high-resolution image is competitive or even superior in quality to images produced by other SR methods.
Image Retrieval: Current Techniques, Promising Directions, and Open Issues
TLDR
The survey includes 100+ papers covering the research aspects of image feature representation and extraction, multidimensional indexing, and system design, three of the fundamental bases of content-based image retrieval.
Deep Image Matting
TLDR
A novel deep learning based algorithm that can tackle image matting problems when an image has similar foreground and background colors or complicated textures and evaluation results demonstrate the superiority of this algorithm over previous methods.
Human age estimation using bio-inspired features
TLDR
This work investigates the biologically inspired features (BIF) for human age estimation from faces with significant improvements in age estimation accuracy over the state-of-the-art methods and proposes a new operator “STD” to encode the aging subtlety on faces.
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