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Found 14 papers, 6 papers with code
Polyp-DAM: Polyp segmentation via depth anything model
In this paper, we unfold a new perspective on polyp segmentation modeling by leveraging the Depth Anything Model (DAM) to provide depth prior to polyp segmentation models.
MixNet: Towards Effective and Efficient UHD Low-Light Image Enhancement
To capture the long-range dependency of features without introducing excessive computational complexity, we present the Global Feature Modulation Layer (GFML).
Joint Projection Learning and Tensor Decomposition Based Incomplete Multi-view Clustering
We further consider the graph noise of projected data caused by missing samples and use a tensor-decomposition based graph filter for robust clustering. JPLTD decomposes the original tensor into an intrinsic tensor and a sparse tensor.
Complex Mixer for MedMNIST Classification Decathlon
With the development of the medical image field, researchers seek to develop a class of datasets to block the need for medical knowledge, such as \text{MedMNIST} (v2).
4K-HAZE: A Dehazing Benchmark with 4K Resolution Hazy and Haze-Free Images
The challenges in building ultra-high-definition (UHD) dehazing datasets are the absence of estimation methods for UHD depth maps, high-quality 4K depth estimation datasets, and migration strategies for UHD haze images from synthetic to real domains.
TabMixer: Excavating Label Distribution Learning with Small-scale Features
Unfortunately, the feature space of the label distribution dataset is affected by human factors and the inductive bias of the feature extractor causing uncertainty in the feature space.
Label distribution learning via label correlation grid
Specifically, we compute a covariance matrix for the label space in the training set to represent the relationships between labels, then model the information distribution (Gaussian distribution function) for each element in the covariance matrix to obtain an LCG.
Label Distribution Learning via Implicit Distribution Representation
Specifically, we use deep implicit representation learning to construct a label distribution matrix with Gaussian prior constraints, where each row component corresponds to the distribution estimate of each label value, and this row component is constrained by a prior Gaussian distribution to moderate the noise and uncertainty interference of the label distribution dataset.
UHD Image Deblurring via Multi-scale Cubic-Mixer
Currently, transformer-based algorithms are making a splash in the domain of image deblurring.
Zero-Reference Image Restoration for Under-Display Camera of UAV
The exposed cameras of UAV can shake, shift, or even malfunction under the influence of harsh weather, while the add-on devices (Dupont lines) are very vulnerable to damage.
Ultra-High-Definition Image Dehazing via Multi-Guided Bilateral Learning
To address the problem, we propose a novel network capable of real-time dehazing of 4K images on a single GPU, which consists of three deep CNNs.
Ultra-High-Definition Image HDR Reconstruction via Collaborative Bilateral Learning
First, we propose a dual-path network to extract content and chromatic features at a reduced resolution of the low dynamic range (LDR) input.
Constrained Bilinear Factorization Multi-view Subspace Clustering
Multi-view clustering is an important and fundamental problem.
Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally
Emotion recognition from facial expressions is an interesting and challenging problem and has attracted much attention in recent years.
