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Found 4 papers, 1 papers with code
Dense Global Context Aware RCNN for Object Detection
RoIPool/RoIAlign is an indispensable process for the typical two-stage object detection algorithm, it is used to rescale the object proposal cropped from the feature pyramid to generate a fixed size feature map.
Global Context Aware RCNN for Object Detection
The core component of our GCA framework is a context aware mechanism, in which both global feature pyramid and attention strategies are used for feature extraction and feature refinement, respectively.
Joint Object Contour Points and Semantics for Instance Segmentation
The attributes of object contours has great significance for instance segmentation task.
Convolutional Neural Networks combined with Runge-Kutta Methods
A convolutional neural network can be constructed using numerical methods for solving dynamical systems, since the forward pass of the network can be regarded as a trajectory of a dynamical system.
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