292 citations · 637 across the 14 of their papers we have counts for
14 papers
INF: Implicit Neural Fusion for LiDAR and Camera
Shuyi Zhou, Shuxiang Xie, Ryoichi Ishikawa +3
Sensor fusion has become a popular topic in robotics. However, conventional fusion methods encounter many difficulties, such as data representation differences, sensor variations,…
Hierarchical Neural Memory Network for Low Latency Event Processing
Ryuhei Hamaguchi, Yasutaka Furukawa, Masaki Onishi +1
This paper proposes a low latency neural network architecture for event-based dense prediction tasks. Conventional architectures encode entire scene contents at a fixed rate regard…
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation
Ryuhei Hamaguchi, Yasutaka Furukawa, Masaki Onishi +1
This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, effic…
Epipolar-Guided Deep Object Matching for Scene Change Detection
Kento Doi, Ryuhei Hamaguchi, Shun Iwase +3
This paper describes a viewpoint-robust object-based change detection network (OBJ-CDNet). Mobile cameras such as drive recorders capture images from different viewpoints each time…
Privacy Preserving Visual SLAM
Mikiya Shibuya, Shinya Sumikura, Ken Sakurada
This study proposes a privacy-preserving Visual SLAM framework for estimating camera poses and performing bundle adjustment with mixed line and point clouds in real time. Previous…
SOIC: Semantic Online Initialization and Calibration for LiDAR and Camera
Weimin Wang, Shohei Nobuhara, Ryosuke Nakamura +1
This paper presents a novel semantic-based online extrinsic calibration approach, SOIC (so, I see), for Light Detection and Ranging (LiDAR) and camera sensors. Previous online cali…
OpenVSLAM: A Versatile Visual SLAM Framework
Shinya Sumikura, Mikiya Shibuya, Ken Sakurada
In this paper, we introduce OpenVSLAM, a visual SLAM framework with high usability and extensibility. Visual SLAM systems are essential for AR devices, autonomous control of robots…
TriDepth: Triangular Patch-based Deep Depth Prediction
Masaya Kaneko, Ken Sakurada, Kiyoharu Aizawa
We propose a novel and efficient representation for single-view depth estimation using Convolutional Neural Networks (CNNs). Point-cloud is generally used for CNN-based 3D scene re…
Rare Event Detection using Disentangled Representation Learning
Ryuhei Hamaguchi, Ken Sakurada, Ryosuke Nakamura
This paper presents a novel method for rare event detection from an image pair with class-imbalanced datasets. A straightforward approach for event detection tasks is to train a de…
Weakly Supervised Silhouette-based Semantic Scene Change Detection
Ken Sakurada, Mikiya Shibuya, Weimin Wang
This paper presents a novel semantic scene change detection scheme with only weak supervision. A straightforward approach for this task is to train a semantic change detection netw…
Scale Estimation of Monocular SfM for a Multi-modal Stereo Camera
Shinya Sumikura, Ken Sakurada, Nobuo Kawaguchi +1
This paper proposes a novel method of estimating the absolute scale of monocular SfM for a multi-modal stereo camera. In the fields of computer vision and robotics, scale estimatio…
Dense Optical Flow based Change Detection Network Robust to Difference of Camera Viewpoints
Ken Sakurada, Weimin Wang, Nobuo Kawaguchi +1
This paper presents a novel method for detecting scene changes from a pair of images with a difference of camera viewpoints using a dense optical flow based change detection networ…
Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets
Kenji Enomoto, Ken Sakurada, Weimin Wang +4
In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to…
Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard
Weimin Wang, Ken Sakurada, Nobuo Kawaguchi
This paper presents a novel method for fully automatic and convenient extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally printed chessboard. The proposed me…