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Found 28 papers, 4 papers with code
Two-Step Color-Polarization Demosaicking Network
Polarization information of light in a scene is valuable for various image processing and computer vision tasks.
PoF: Post-Training of Feature Extractor for Improving Generalization
We developed a training algorithm called PoF: Post-Training of Feature Extractor that updates the feature extractor part of an already-trained deep model to search a flatter minimum.
Multi-Modal Pedestrian Detection with Large Misalignment Based on Modal-Wise Regression and Multi-Modal IoU
Due to this assumption's breakdown, the position of the bounding boxes does not match between the two modalities, resulting in a significant decrease in detection accuracy, especially in regions where the amount of misalignment is large.
Geometric Data Augmentation Based on Feature Map Ensemble
The performance of CNN is dramatically degraded by geometric transformation, such as large rotations.
Hyper Suprime-Cam Legacy Archive
HSC is an optical wide-field imager installed at the prime focus of the Subaru Telescope and has been in operation since 2014.
Instrumentation and Methods for Astrophysics Astrophysics of Galaxies
Deep Snapshot HDR Imaging Using Multi-Exposure Color Filter Array
In this paper, we propose a deep snapshot high dynamic range (HDR) imaging framework that can effectively reconstruct an HDR image from the RAW data captured using a multi-exposure color filter array (ME-CFA), which consists of a mosaic pattern of RGB filters with different exposure levels.
Adaptive Future Frame Prediction with Ensemble Network
A common limitation of the existing learning-based approaches is a mismatch of training data and test data.
Human Segmentation with Dynamic LiDAR Data
It has a two-branch structure, i. e., the spatial segmentation branch and the temporal velocity estimation branch.
Monochrome and Color Polarization Demosaicking Using Edge-Aware Residual Interpolation
Since the polarimeter consists of an image sensor equipped with a monochrome or color polarization filter array (MPFA or CPFA), the demosaicking process to interpolate missing pixel values plays a crucial role in obtaining high-quality polarization images.
Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering
The usage of convolutional neural networks (CNNs) for unsupervised image segmentation was investigated in this study.
Classifying degraded images over various levels of degradation
Classification for degraded images having various levels of degradation is very important in practical applications.
Learning-Based Human Segmentation and Velocity Estimation Using Automatic Labeled LiDAR Sequence for Training
In this paper, we propose an automatic labeled sequential data generation pipeline for human segmentation and velocity estimation with point clouds.
Block-wise Scrambled Image Recognition Using Adaptation Network
In this study, a perceptually hidden object-recognition method is investigated to generate secure images recognizable by humans but not machines.
New Perspective of Interpretability of Deep Neural Networks
Improving the interpretability of DNNs is one of the hot research topics.
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
This study addresses an issue of co-adaptation between a feature extractor and a classifier in a neural network.
Intentional Attention Mask Transformation for Robust CNN Classification
To tackle this problem, we exploit a multi-channel attention mechanism in feature space.
Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks
To tackle this problem, we exploit a multi-channel attention mechanism in feature space.
Improving Transparency of Deep Neural Inference Process
However, the inference process of deep learning is black-box, and not very suitable to safety-critical systems which must exhibit high transparency.
Automatic Labeled LiDAR Data Generation based on Precise Human Model
We present 500k+ data generated by the proposed pipeline.
Estimation and Restoration of Compositional Degradation Using Convolutional Neural Networks
However, image degradations in practice are often a mixture of several types of degradation.
Weighted Sigmoid Gate Unit for an Activation Function of Deep Neural Network
In this paper, a weighted sigmoid gate unit (WiG) is proposed as the activation function.
Gradient-Based Low-Light Image Enhancement
A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones.
Non-blind Image Restoration Based on Convolutional Neural Network
Blind image restoration processors based on convolutional neural network (CNN) are intensively researched because of their high performance.
Network Analysis for Explanation
Safety critical systems strongly require the quality aspects of artificial intelligence including explainability.
Misalignment-Robust Joint Filter for Cross-Modal Image Pairs
Next, the joint-filter cost volume and a set of filtered images are computed from the target image and the set of the translated guidances.
Photometric Redshifts for Hyper Suprime-Cam Subaru Strategic Program Data Release 1
Photometric redshifts are a key component of many science objectives in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP).
Astrophysics of Galaxies
Gradient-Domain Image Reconstruction Framework With Intensity-Range and Base-Structure Constraints
To generate detail-preserving and artifact-free output images, we combine the benefits of the two approaches into the proposed framework by introducing the intensity-range constraint and the base-structure constraint.
