Robotics and Computer Vision Lab

Publications

Extra Form
저 자 Dongshin Kim, Seunghak Shin, In So Kweon
학 회 IEEE Transactions on Automation Science and Engineering (TASE)
Notes accepted
논문일시(Year) 2017
논문일시(Month) 11
Inertial Measurement Units (IMU) are successfully utilized to compensate localization errors in sensor fused inertial navigation systems. An IMU generally produces high frequency signals ranging from hundreds to thousands of Hz, and preintegration methods are applied to effectively process these high frequency signals for inertial navigation systems. The main problem with an existing preintegration method is that the inertial propagation models in the method are only generated at the IMU's coordinate system. Hence, the models have to be converted to the coordinate system of the other sensor in order to apply its constraint. So the iterative optimization framework using the conventional method takes large amount of time. In addition, since a general rigid body transformation can not transfer a velocity propagation model to the other coordinate system, the concept of relative motion analysis needs to be considered. To solve the problems above, in this paper, we propose a novel relative preintegration method that can generate inertial propagation models at any sensor's coordinate system in a rigid body. This permits accurate and fast IMU processing in sensor fused inertial navigation systems. We applied new non-linear optimization frameworks to solve initialization and extrinsic calibration problems for the IMU-IMU, IMU-Camera, and IMU-LiDAR pair based on the proposed relative preintegration method in an on-line manner, and the superior results of the mentioned processes are presented as well.

List of Articles
605. Align-and-Attend Network for Globally and Locally Coherent Video Inpainting
Sanghyun Woo, Dahun Kim, KwanYong Park, Joon-Young Lee, In So Kweon
British Machine Vision Conference (BMVC) 2020 / 09
604. Non-Local Spatial Propagation Network for Depth Completion
Jinsun Park, Kyungdon Joo, Zhe Hu, Chi-Kuei Liu, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
603. Two-Phase Pseudo Label Densification for Self-training based Domain Adaptation
Inkyu Shin, Sanghyun Woo, Fei Pan, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
602. Global-and-Local Relative Position Embedding for Unsupervised Video Summarization
Yunjae Jung, Donghyeon Cho, Sanghyun Woo, In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
601. Detecting Human-Object Interactions with Action Co-occurrence Priors
Dong-Jin Kim, Xiao Sun, Jinsoo Choi, Stephen Lin, and In So Kweon
European Conference on Computer Vision (ECCV) 2020 / 08
600. SideGuide: A Large-scale Sidewalk Dataset for Guiding Impaired People
Kibaek Park*, Youngtaek Oh*, Soomin Ham*, Kyungdon Joo*, HYOKYOUNG KIM, HyoYoung Kum, In So Kweon
IROS, 2020 2020 / 10
599. Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations
Chaoning Zhang*, Philipp Benz*, Tooba Imtiaz, In So Kweon (Chaoning Zhang, Philipp Benz are co-first author)
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
598. Video Panoptic Segmentation
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
597. Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
596. Robust Reference-based Super-Resolution with Similarity-Aware Deformable Convolution
Gyumin Shim, Jinsun Park, In So Kweon
Computer Vision and Pattern Recognition, CVPR, 2020. 2020 / 06
595. Salient View Selection for Visual Recognition of Industrial Components
Seong-heum Kim, Gyeongmin Choe, Min-Gyu Park, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
594. Linear RGB-D SLAM for Atlanta World
Kyungdon Joo, Tae-Hyun Oh, Francois Rameau, Jean-Charles Bazin and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
593. Globally Optimal Relative Pose Estimation for Camera on a Selfie Stick
Kyungdon Joo, Hongdong Li, Tae-Hyun Oh, Yunsu Bok and and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
592. CNN-based Simultaneous Dehazing and Depth Estimation
Byeong-Uk Lee, Kyunghyun Lee, Jean Oh and In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2020 / 05
591. Depth Completion with Deep Geometry and Context Guidance
Byeong-Uk Lee, Hae-Gon Jeon, Sunghoon Im, In So Kweon
IEEE International Conference on Robotics and Automation (ICRA) 2019 / 05
590. A Simple and Light-weight Attention Module for Convolutional Neural Networks
Jongchan Park*, Sanghyun Woo*, Joon-Young Lee, In-So Kweon
International Journal of Computer Vision (IJCV) 2019 / 12
589. Recurrent Temporal Aggregation Framework for Deep Video Inpainting
Dahun Kim*, Sanghyun Woo*, Joon-Young Lee, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019 / 11
588. Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications
Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2019 / 10
587. Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling
Yunjae Jung, Dahun Kim, Sanghyun Woo, Kyungsu Kim, Sungjin Kim, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2020 / 02
586. CD-UAP: Class Discriminative Universal Adversarial Perturbations
Chaoning Zhang*, Philipp Benz*, Tooba Imtiaz, In-So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2020 / 02
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