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Found 4 papers, 2 papers with code
Real-World Efficient Blind Motion Deblurring via Blur Pixel Discretization
As recent advances in mobile camera technology have enabled the capability to capture high-resolution images, such as 4K images, the demand for an efficient deblurring model handling large motion has increased.
KL-Divergence-Based Region Proposal Network for Object Detection
The learning of the region proposal in object detection using the deep neural networks (DNN) is divided into two tasks: binary classification and bounding box regression task.
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image
Instead of assigning each ground truth to specific locations of network's output, we train a network by estimating the probability density of bounding boxes in an input image using a mixture model.
C3: Concentrated-Comprehensive Convolution and its application to semantic segmentation
To resolve this problem, we propose a new block called Concentrated-Comprehensive Convolution (C3) which applies the asymmetric convolutions before the depth-wise separable dilated convolution to compensate for the information loss due to dilated convolution.
