Robotics and Computer Vision Lab

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저 자 Namil Kim, Yukyung Choi, Soonmin Hwang, In So Kweon
학 회 Association for the Advancement of Artificial Intelligence (AAAI)
Notes This work was supported by the Development of Autonomous Emergency Braking System for Pedestrian Protection project funded by the Ministry of Trade, Industry and Energy of Korea (MOTIE)(No.10044775). We also supported to gold prize from 23th HumanTech Paper Award in Samsung.
논문일시(Year) 2018
논문일시(Month) 02
http://multispectral.kaist.ac.kr** The first and second authors contributed equally to this work.

To understand the real-world, it is essential to perceive in all-day conditions including cases which are not suitable for RGB sensors, especially at night. Beyond these limitations, the innovation introduced here is a multispectral solution in the form of depth estimation from an illumination- invariant thermal sensor without an additional depth sensor. Based on an analysis of multispectral properties and the relevance to depth predictions, we propose an efficient and novel multi-task framework called the Multispectral Transfer Net- work (MTN) to estimate a depth image from a single thermal image. By exploiting geometric priors and chromaticity clues, our model can generate a pixel-wise depth image in an unsupervised manner. Moreover, we propose a new type of multitask module called Interleaver as a means of incorporating the chromaticity and fine details of skip-connections into the depth estimation framework without sharing feature layers. Lastly, we explain a novel technical means of stably training and covering large disparities and extending thermal images to data-driven methods for all-day conditions. In experiments, we demonstrate the better performance and generalization of depth estimation through the proposed multispectral stereo dataset, including various driving conditions.

List of Articles
542. KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving
Yukyung Choi, Namil Kim, Soonmin Hwang, Kibaek Park, Jae Shin Yoon, Kyunghwan An and In So Kweon
Transactions on Intelligent Transportation Systems (T-ITS) 2018 / 03
541. RANUS: RGB and NIR Urban Scene Dataset for Deep Scene Parsing
Gyeongmin Choe, Seong-heum Kim, Sunghoon Im, Joon-Young Lee, Srinivasa Narasimhan, In So Kweon
IEEE Robotics and Automation Letters (RAL) 2018 / 02
540. Contextually Customized Video Summaries via Natural Language
Jinsoo Choi, Tae-Hyun Oh, In So Kweon
IEEE Winter Conf. on Applications of Computer Vision (WACV) 2018 / 03
539. Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution
Oleksandr Bailo , Francois Rameau , Kyungdon Joo , Jinsun Park , Oleksandr Bogdan , In So Kweon
Pattern Recognition Letters (PRL) 2018 / 02
538. Disjoint Multi-task Learning between Heterogeneous Human-centric Tasks
Dong-Jin Kim , Jinsoo Choi , Tae-Hyun Oh , Youngjin Yoon , In So Kweon
IEEE Winter Conf. on Applications of Computer Vision (WACV) 2018 / 03
537. Learning Image Representations by Completing Damaged Jigsaw Puzzles
Dahun Kim , Donghyeon Cho , Donggeun Yoo , In So Kweon
IEEE Winter Conf. on Applications of Computer Vision (WACV) 2018 / 05
536. StairNet: Top-Down Semantic Aggregation for Accurate One Shot Detection
Sanghyun Woo, Soonmin Hwang, In So Kweon
IEEE Winter Conf. on Applications of Computer Vision (WACV) 2018 / 03
» Multispectral Transfer Network: Unsupervised Depth Estimation for All-day Vision
Namil Kim, Yukyung Choi, Soonmin Hwang, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2018 / 02
534. Co-domain Embedding using Deep Quadruplet Network for Unseen Traffic Sign Recognition
Junsik Kim, Seokju Lee, Tae-Hyun Oh, In So Kweon
Association for the Advancement of Artificial Intelligence (AAAI) 2018 / 02
533. On-line Initialization and Extrinsic Calibration of an Inertial Navigation System with a Relative Preintegration Method on Manifold
Dongshin Kim, Seunghak Shin, In So Kweon
IEEE Transactions on Automation Science and Engineering (TASE) 2017 / 11
532. Robust and Globally Optimal Manhattan Frame Estimation in Near Real Time
Kyungdon Joo, Tae-Hyun Oh, Junsik Kim, In So Kweon
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2017 / 11
531. Geometry Guided 3D Propagation for Depth from Small Motion
Seunghak Shin, Sunghoon Im, Inwook Shim, Hae-Gon Jeon, In So Kweon
IEEE Signal Processing Letters 2017 / 12
530. Intelligent Assistant for People with Low Vision Abilities
Oleksandr Bogdan, Oleg Yurchenko, Oleksandr Bailo, Francois Rameau, Donggeun Yoo, In So Kweon
The 8th Pacific Rim Symposium on Image and Video Technology (PSIVT) 2017 / 11
529. Multi-Scale, Multi-Object and Real-Time Face Detection and Head Pose Estimation Using Deep Neural Networks
Byungtae Ahn, Dong-Geol Choi, In So Kweon
Journal of Korea Robotics Society 2017 / 09
528. VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
Seokju Lee, Junsik Kim, Jae Shin Yoon, Seunghak Shin, Oleksandr Bailo, Namil Kim, Tae-Hee Lee, Hyun Seok Hong, Seung-Hoon Han, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
527. Two-Phase Learning for Weakly Supervised Object Localization
Dahun Kim, Donghyeon Cho, Donggeun Yoo, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
526. Weakly- and Self- Supervised Learning for Content-Aware Deep Image Retargeting
Donghyeon Cho, Jinsun Park, Tae-Hyun Oh, Yu-Wing Tai, In So Kweon
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
525. Deltille Grids for Geometric Camera Calibration
Hyowon Ha, Michal Perdoch, Hatem Alismail, In So Kweon, Yaser Sheikh
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
524. Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning
Tae-Hyun Oh, Kyungdon Joo, Neel Joshi, Baoyuan Wang, In So Kweon, Sing Bing Kang
IEEE International Conference on Computer Vision (ICCV) 2017 / 10
523. Noise Robust Depth From Focus Using a Ring Difference Filter
Jaeheung Surh, Hae-Gon Jeon, Yunwon Park, Sunghoon Im, Hyowon Ha, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 / 07
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