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Single Image Dehazing via Multi-scale Convolutional Neural Networks
TLDR
A multi-scale deep neural network for single-image dehazing by learning the mapping between hazy images and their corresponding transmission maps by combining a coarse-scale net which predicts a holistic transmission map based on the entire image, and a fine-scale network which refines results locally.
Cluster-Based Co-Saliency Detection
TLDR
This paper introduces a new cluster-based algorithm for co-saliency detection that is mostly bottom-up without heavy learning, and outperforms most the state-of-the-art saliency detection methods.
Gated Fusion Network for Single Image Dehazing
TLDR
An efficient algorithm to directly restore a clear image from a hazy input using an end-to-end trainable neural network that consists of an encoder and a decoder is proposed.
Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
TLDR
A deep learning architecture, named M-Net, is proposed, which solves the OD and OC segmentation jointly in a one-stage multi-label system and introduces the polar transformation, which provides the representation of the original image in the polar coordinate system.
Depth Enhanced Saliency Detection Method
TLDR
This paper proposes a saliency detection method using the additional depth information and saliency cues are provided to follow the laws of the visually salient stimuli in both color and depth spaces.
Low-Rank Tensor Constrained Multiview Subspace Clustering
TLDR
A low-rank tensor constraint is introduced to explore the complementary information from multiple views and, accordingly, a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC) is established.
Diversity-induced Multi-view Subspace Clustering
TLDR
A multi-view clustering framework, called Diversity-induced Multi-view Subspace Clustering (DiMSC), is proposed for this task, which extends the existing subspace clustering into the multi- view domain, and utilizes the Hilbert Schmidt Independence Criterion (HSIC) as a diversity term to explore the complementarity of multi-View representations.
Total Variation Regularized RPCA for Irregularly Moving Object Detection Under Dynamic Background
TLDR
This paper presents a unified framework for addressing the difficulties mentioned above, especially the one caused by irregular object movement, and significantly outperforms the state-of-the-art approaches, especially for the cases with dynamic backgrounds and discontinuous movements.
Image Deblurring via Extreme Channels Prior
TLDR
This work observes that the bright pixels in the clear images are not likely to be bright after the blur process, and proposes a technique fordeblurring such images which elevates the performance of existing motion deblurring algorithms and takes advantage of both Bright and Dark Channel Prior.
Self-Adaptively Weighted Co-Saliency Detection via Rank Constraint
TLDR
A general saliency map fusion framework, which exploits the relationship of multiple saliency cues and obtains the self-adaptive weight to generate the final saliency/co-saliency map.
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