Robotics and Computer Vision Lab

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저 자 Seunghak Shin, Sunghoon Im, Inwook Shim, Hae-Gon Jeon, In So Kweon
학 회 IEEE Signal Processing Letters
Notes This work was supported by the “Development of core technology for advanced locomotion/manipulation based on high-speed/power robot platform and robot intelligence,” project from the Korea Evaluation Institute of Industrial Technology of the Republic of Korea. The work of S. Im and H.-G. Jeon was supported in part by Global Ph.D. Fellowship Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant NRF-2016907531 and Grant NRF-2015034617.
논문일시(Year) 2017
논문일시(Month) 12
http://ieeexplore.ieee.org/document/8063412/In this letter, we present an accurate Depth from Small Motion approach, which reconstructs three-dimensional (3-D) depth from image sequences with extremely narrow base-lines.We start with estimating sparse 3-D points and camera poses via the structure from motion method. For dense depth reconstruction, we propose a novel depth propagation using a geometric guidance term that considers not only the geometric constraint from the surface normal, but also color consistency. In addition, we propose an accurate surface normal estimation method with a multiple range search so that the normal vector can guide the direction of the depth propagation precisely. The major benefit of our depth propagation method is that it obtains detailed structures of a scene without fronto-parallel bias.We validate our method using various indoor and outdoor datasets, and both qualitative and quantitative experimental results show that our new algorithm consistently generates better 3-D depth information than the results of existing state-of-the-art methods.

List of Articles
563. Gated Bidirectional Feature Pyramid Network for Accurate One Shot Detection
Sanghyun Woo, Soonmin Hwang, Ho-Deok Jang, In So Kweon
Machine Vision And Applications (MVA) 2019 / 1
562. High-Fidelity Depth Upsampling Using the Self-Learning Framework
Inwook Shim, Tae-Hyun Oh, In So Kweon
Sensors 2019 / 01
561. DPSNet: End-to-end Deep Plane Sweep Stereo
Sunghoon Im, Hae-Gon Jeon, Stephen Lin, In So Kweon
International Conference on Learning Representations (ICLR) 2019 / 05
560. Robust Depth Estimation using Auto-Exposure Bracketing
Sunghoon Im, Hae-Gon Jeon, In So Kweon
IEEE Transaction on Image Processing (TIP) 2018 / 12
559. Part-based Player Identification using Deep Convolutional Representation and Multi-scale Pooling
Arda Senocak, Tae-Hyun Oh, Junsik Kim, In So Kweon
Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2018 / 06
558. Discriminative Feature Learning for Unsupervised Video Summarization
Yunjae Jung, Donghyeon Cho, Dahun Kim, Sanghyun Woo, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2019 / 01
557. Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles
Dahun Kim, Donghyeon Cho, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2019 / 01
556. Semi-calibrated Photometric Stereo
Donghyeon Cho, Yasuyuki Matsushita, Yu-Wing Tai, and In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) /
555. Deep Convolutional Neural Network for Natural Image Matting using Initial Alpha Mattes
Donghyeon Cho, Yu-Wing Tai, In So Kweon
IEEE Transactions on Image Processing (TIP), accepted /
554. LinkNet: Relational Embedding for Scene Graph
Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon
Neural Information Processing Systems (NIPS) 2018 / 12
553. CBAM: Convolutional Block Attention Module
Jongchan Park, Sanghyun Woo, Joon-Young Lee, In So Kweon
European Conference on Computer Vision (ECCV) 2018 / 09
552. BAM: Bottleneck Attention Module
Jongchan Park, Sanghyun Woo, Joon-Young Lee, In So Kweon
British Machine Vision Conference (BMVC) 2018 / 09
551. Robust Low-rank Optimization with Priors
Tae-Hyun Oh
KAIST 2017 / 5
550. EPINET: A Fully-Convolutional Neural Network using Epipolar Geometry for Depth from Light Field Images
Changha Shin, Hae-Gon Jeon, Youngjin Yoon, In So Kweon, Seon Joo Kim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 / 06
549. Distort-and-Recover: Color Enhancement using Deep Reinforcement Learning
Jongchan Park, Joon-Young Lee, Donggeun Yoo, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 / 06
548. Robust Depth Estimation from Auto Bracketed Images
Sunghoon Im, Hae-Gon Jeon, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 / 06
547. Learning to Localize Sound Source in Visual Scenes
Arda Senocak, Tae-Hyun Oh, Junsik Kim, Ming-Hsuan Yang, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 2018 / 06
546. Globally Optimal Inlier Set Maximization for Atlanta Frame Estimation
Kyungdon Joo, Tae-Hyun Oh, In So Kweon, Jean-Charles Bazin
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 / 06
545. Real-Time Head Pose Estimation using Multi-Task Deep Neural Network
Byungtae Ahn, Dong-Geol Choi, Jaesik Park, In So Kweon
Robotics and Autonomous Systems 2018 / 05
544. Depth from a Light Field Image with Learning-based Matching Costs
Hae-Gon Jeon, Jaesik Park, Gyeongmin Choe, Jinsun Park, Yunsu Bok, Yu-Wing Tai and In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2018 / 01.15
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