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Found 6 papers, 3 papers with code
Cross-Image Region Mining with Region Prototypical Network for Weakly Supervised Segmentation
To improve the generality of the objective activation maps, we propose a region prototypical network RPNet to explore the cross-image object diversity of the training set.
Motion-Guided Cascaded Refinement Network for Video Object Segmentation
Then, the proposed Cascaded Refinement Network(CRN) takes the coarse segmentation as guidance to generate an accurate segmentation of full resolution.
Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification
Typical person re-identification (ReID) methods usually describe each pedestrian with a single feature vector and match them in a task-specific metric space.
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
We propose a novel approach for cost-adjustable inference in CNNs - Stochastic Downsampling Point (SDPoint).
Microscopic Muscle Image Enhancement
Ring artifacts problems are addressed and a kernel propagation strategy is proposed to speedup the algorithm and deals with the high non-uniformity of the blur kernels on muscle images.
DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information Inflows
Deluge Networks (DelugeNets) are deep neural networks which efficiently facilitate massive cross-layer information inflows from preceding layers to succeeding layers.
