A survey on instance segmentation: state of the art
Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …
digital image inference. It not only provides the classes of the image objects, but also …
Non-local neural networks
Both convolutional and recurrent operations are building blocks that process one local
neighborhood at a time. In this paper, we present non-local operations as a generic family of …
neighborhood at a time. In this paper, we present non-local operations as a generic family of …
Deep joint rain detection and removal from a single image
In this paper, we address a rain removal problem from a single image, even in the presence
of heavy rain and rain streak accumulation. Our core ideas lie in our new rain image model …
of heavy rain and rain streak accumulation. Our core ideas lie in our new rain image model …
Deep HDR imaging via a non-local network
One of the most challenging problems in reconstructing a high dynamic range (HDR) image
from multiple low dynamic range (LDR) inputs is the ghosting artifacts caused by the object …
from multiple low dynamic range (LDR) inputs is the ghosting artifacts caused by the object …
A machine learning approach for non-blind image deconvolution
CJ Schuler, H Christopher Burger… - Proceedings of the …, 2013 - cv-foundation.org
Image deconvolution is the ill-posed problem of recovering a sharp image, given a blurry
one generated by a convolution. In this work, we deal with space-invariant nonblind …
one generated by a convolution. In this work, we deal with space-invariant nonblind …
[HTML][HTML] Artifact removal using improved GoogLeNet for sparse-view CT reconstruction
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with
both accelerated scan and reduced projection/back-projection calculation. Despite the rapid …
both accelerated scan and reduced projection/back-projection calculation. Despite the rapid …
Progressive sparse local attention for video object detection
Transferring image-based object detectors to the domain of videos remains a challenging
problem. Previous efforts mostly exploit optical flow to propagate features across frames …
problem. Previous efforts mostly exploit optical flow to propagate features across frames …
Improving low-dose CT image using residual convolutional network
Low-dose CT is an effective solution to alleviate radiation risk to patients, it also introduces
additional noise and streak artifacts. In order to maintain a high image quality for low-dose …
additional noise and streak artifacts. In order to maintain a high image quality for low-dose …
Global pose estimation with an attention-based recurrent network
The ability for an agent to localize itself within an environment is crucial for many real-world
applications. For unknown environments, Simultaneous Localization and Mapping (SLAM) …
applications. For unknown environments, Simultaneous Localization and Mapping (SLAM) …
Non-local auto-encoder with collaborative stabilization for image restoration
Deep neural networks have been applied to image restoration to achieve the top-level
performance. From a neuroscience perspective, the layerwise abstraction of knowledge in a …
performance. From a neuroscience perspective, the layerwise abstraction of knowledge in a …