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Found 7 papers, 0 papers with code
Use square root affinity to regress labels in semantic segmentation
Specifically, we utilize the label to generate a multi-scale label affinity matrix as a structural supervision, and we use a square root kernel to compute a non-local affinity matrix on output layers.
Multi-Instance Learning by Utilizing Structural Relationship among Instances
Multi-Instance Learning(MIL) aims to learn the mapping between a bag of instances and the bag-level label.
A Group Norm Regularized Factorization Model for Subspace Segmentation
Subspace segmentation assumes that data comes from the union of different subspaces and the purpose of segmentation is to partition the data into the corresponding subspace.
A Uniform Generalization Error Bound for Generative Adversarial Networks
To better understand the unsupervised model, GANs, we establish the generalization bound, which uniformly holds with respect to the choice of generators.
DG-GAN: the GAN with the duality gap
Generative Adversarial Networks (GANs) are powerful, but difficult to understand and train because GANs is a min-max problem.
Geometric Operator Convolutional Neural Network
The Convolutional Neural Network (CNN) has been successfully applied in many fields during recent decades; however it lacks the ability to utilize prior domain knowledge when dealing with many realistic problems.
Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention
Video-based person re-identification (ReID) is a challenging problem, where some video tracks of people across non-overlapping cameras are available for matching.
