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Found 17 papers, 1 papers with code
Adjacency-hopping de Bruijn Sequences for Non-repetitive Coding
A special type of cyclic sequences named adjacency-hopping de Bruijn sequences is introduced in this paper.
Single Image Deraining via Feature-based Deep Convolutional Neural Network
A single image deraining algorithm based on the combination of data-driven and model-based approaches is proposed.
Part Aware Contrastive Learning for Self-Supervised Action Recognition
This paper proposes an attention-based contrastive learning framework for skeleton representation learning, called SkeAttnCLR, which integrates local similarity and global features for skeleton-based action representations.
Efficient Robust Principal Component Analysis via Block Krylov Iteration and CUR Decomposition
Specifically, the Krylov iteration method is employed to approximate the eigenvalue decomposition in the rank estimation, which requires O(ndrq + n(rq)^2) for an (nxd) input matrix, in which q is a parameter with a small value, r is the target rank.
Single Image Deraining via Rain-Steaks Aware Deep Convolutional Neural Network
It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image.
Dual-Scale Single Image Dehazing Via Neural Augmentation
Model-based single image dehazing algorithms restore haze-free images with sharp edges and rich details for real-world hazy images at the expense of low PSNR and SSIM values for synthetic hazy images.
SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition
Given the unmasked skeleton sequence, the encoder is fine-tuned for the action recognition task.
Adaptive Weighted Guided Image Filtering for Depth Enhancement in Shape-From-Focus
In order to preserve the edges accurately in the refined depth map, the guidance image is constructed from the multi-focus image sequence, and the coefficient of the AWGIF is utilized to suppress the noise while enhancing the fine depth details.
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Spectral Reconstruction
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Model-Based Single Image Deep Dehazing
Model-based single image dehazing algorithms restore images with sharp edges and rich details at the expense of low PSNR values.
Hybrid Saturation Restoration for LDR Images of HDR Scenes
It is an ill-posed problem to restore the saturated regions of the LDR image.
Single image dehazing via combining the prior knowledge and CNNs
If the transmission map of a pixel is small, the base layer of the haze image is used to recover a haze-free image via atmospheric scattering model, finally.
Adaptive Rank Estimate in Robust Principal Component Analysis
In this paper, an adaptive rank estimate based RPCA (ARE-RPCA) is proposed, which adaptively assigns weights on different singular values via rank estimation.
Single Image Brightening via Multi-Scale Exposure Fusion with Hybrid Learning
In this paper, a single image brightening algorithm is introduced to brighten such an image.
Illumination Normalization via Merging Locally Enhanced Textures for Robust Face Recognition
Finally, the local contrast equalization (LCE) is performed on the fused face image to reduce the influence caused by over or under saturated pixel values in highlight or dark regions.
Exposure Interpolation by Combining Model-driven and Data-driven Methods
A natural question raised here is "Is there any space for conventional methods on these problems?"
A novel online multi-label classifier for high-speed streaming data applications
In this paper, a high-speed online neural network classifier based on extreme learning machines for multi-label classification is proposed.
A Novel Online Real-time Classifier for Multi-label Data Streams
In this paper, a novel extreme learning machine based online multi-label classifier for real-time data streams is proposed.
