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CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation
Video instance segmentation is a complex task in which we need to detect...
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Outlier Detection Using a Novel method: Quantum Clustering
We propose a new assumption in outlier detection: Normal data instances ...
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Neural Sparse Representation for Image Restoration
Inspired by the robustness and efficiency of sparse representation in sp...
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Quantum-Classical Machine learning by Hybrid Tensor Networks
Tensor networks (TN) have found a wide use in machine learning, and in p...
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Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks
Conventional learning-based approaches to low-light image enhancement ty...
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Pyramid Attention Networks for Image Restoration
Self-similarity refers to the image prior widely used in image restorati...
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Scale-wise Convolution for Image Restoration
While scale-invariant modeling has substantially boosted the performance...
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DAVID: Dual-Attentional Video Deblurring
Blind video deblurring restores sharp frames from a blurry sequence with...
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Information Bottleneck Methods on Convolutional Neural Networks
Recent year, many researches attempt to open the black box of deep neura...
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EnlightenGAN: Deep Light Enhancement without Paired Supervision
Deep learning-based methods have achieved remarkable success in image re...
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Generative Tensor Network Classification Model for Supervised Machine Learning
Tensor network (TN) has recently triggered extensive interests in develo...
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Connecting Image Denoising and High-Level Vision Tasks via Deep Learning
Image denoising and high-level vision tasks are usually handled independ...
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U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting
This paper studies the challenging problem of fingerprint image denoisin...
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Non-Local Recurrent Network for Image Restoration
Many classic methods have shown non-local self-similarity in natural ima...
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Image Super-Resolution via Dual-State Recurrent Networks
Advances in image super-resolution (SR) have recently benefited signific...
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Survey of Face Detection on Low-quality Images
Face detection is a well-explored problem. Many challenges on face detec...
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Learning Simple Thresholded Features with Sparse Support Recovery
The thresholded feature has recently emerged as an extremely efficient, ...
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Enhance Visual Recognition under Adverse Conditions via Deep Networks
Visual recognition under adverse conditions is a very important and chal...
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Learning Object Detectors from Scratch with Gated Recurrent Feature Pyramids
In this paper, we propose gated recurrent feature pyramid for the proble...
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Machine Learning by Two-Dimensional Hierarchical Tensor Networks: A Quantum Information Theoretic Perspective on Deep Architectures
The resemblance between the methods used in studying quantum-many body p...
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Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach
Emotion recognition from facial expressions is tremendously useful, espe...
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Learning Audio Sequence Representations for Acoustic Event Classification
Acoustic Event Classification (AEC) has become a significant task for ma...
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When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach
Conventionally, image denoising and high-level vision tasks are handled ...
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Understanding Convolution for Semantic Segmentation
Recent advances in deep learning, especially deep convolutional neural n...
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Learning a Mixture of Deep Networks for Single Image Super-Resolution
Single image super-resolution (SR) is an ill-posed problem which aims to...
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Brain-Inspired Deep Networks for Image Aesthetics Assessment
Image aesthetics assessment has been challenging due to its subjective n...
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Studying Very Low Resolution Recognition Using Deep Networks
Visual recognition research often assumes a sufficient resolution of the...
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D^3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images
In this paper, we design a Deep Dual-Domain (D^3) based fast restoration...
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Deep Networks for Image Super-Resolution with Sparse Prior
Deep learning techniques have been successfully applied in many areas of...
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