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Found 10 papers, 3 papers with code
TSC: A Simple Two-Sided Constraint against Over-Smoothing
Meanwhile, the contrastive constraint, applied to the representation matrix's rows, enhances the discriminability of the nodes.
Deep Embedding Clustering Driven by Sample Stability
To address this issue, we propose a deep embedding clustering algorithm driven by sample stability (DECS), which eliminates the requirement of pseudo targets.
2D Human Pose Estimation with Explicit Anatomical Keypoints Structure Constraints
Recently, human pose estimation mainly focuses on how to design a more effective and better deep network structure as human features extractor, and most designed feature extraction networks only introduce the position of each anatomical keypoint to guide their training process.
Sparse Regularized Correlation Filter for UAV Object Tracking with adaptive Contextual Learning and Keyfilter Selection
Another approaches can alleviate the temporal degeneration of learned filters by introducing the temporal regularizer, which depends on the assumption that the filers between consecutive frames should be coherent.
Linear Array Network for Low-light Image Enhancement
However, the convolution operation is based on a local sliding window mechanism, which is difficult to construct the long-range dependencies of the feature maps.
Progressive residual learning for single image dehazing
The recent physical model-free dehazing methods have achieved state-of-the-art performances.
Extreme Low-Light Imaging with Multi-granulation Cooperative Networks
Low-light imaging is challenging since images may appear to be dark and noised due to low signal-to-noise ratio, complex image content, and the variety in shooting scenes in extreme low-light condition.
Latent Complete Row Space Recovery for Multi-view Subspace Clustering
LCRSR is able to recover the row space of the latent representation, which not only carries complete information from multiple views but also determines the subspace membership under certain conditions.
Logic could be learned from images
This task is to learn and reason the logic relation from images, without presetting any reasoning patterns.
Part-based Visual Tracking via Structural Support Correlation Filter
In addition, to mitigate the issue of drift away from object further, we introduce inter-frame consistencies of local parts into our model.
