Robotics and Computer Vision Lab

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저 자 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
학 회 IEEE International Conference on Computer Vision (ICCV)
논문일시(Year) 2017
논문일시(Month) 10
https://github.com/SeokjuLee/VPGNetIn this paper, we propose a unified end-to-end trainable multi-task network that jointly handles lane and road marking detection and recognition that is guided by a vanishing point under adverse weather conditions. We tackle rainy and low illumination conditions, which have not been extensively studied until now due to clear challenges. For example, images taken under rainy days are subject to low illumination, while wet roads cause light reflection and distort the appearance of lane and road markings. At night, color distortion occurs under limited illumination. As a result, no benchmark dataset exists and only a few developed algorithms work under poor weather conditions. To address this shortcoming, we build up a lane and road marking benchmark which consists of about 20,000 images with 17 lane and road marking classes under four different scenarios: no rain, rain, heavy rain, and night. We train and evaluate several versions of the proposed multi-task network and validate the importance of each task. The resulting approach, VPGNet, can detect and classify lanes and road markings, and predict a vanishing point with a single forward pass. Experimental results show that our approach achieves high accuracy and robustness under various conditions in real-time (20 fps). The benchmark and the VPGNet model will be publicly available.

List of Articles
315. Camera Exposure Control for Robust Robot Vision with Noise-Aware Image Quality Assessment
Ukcheol Shin, Jinsun Park, Gyumin Shim, Francois Rameau, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
314. Learning Residual Flow as Dynamic Motion from Stereo Videos
Seokju Lee, Sunghoon Im, Stephen Lin, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
313. DISC: A Large-scale Virtual Dataset for Simulating Disaster Scenarios
Hae-Gon Jeon, Sunghoon Im, Byeong-Uk Lee, Dong-Geol Choi, Martial Hebert, and In So Kweon
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE 2019 / 11
312. Segment2Regress: Monocular 3D Vehicle Localization in Two Stages
Jaesung Choe, Kyungdon Joo, Francois Rameau, Gyumin Shim, In So Kweon
Robotics: Science and Systems (RSS) 2019 / 06
311. Deep Video Inpainting
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
310. Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence
Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
309. Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning
Dong-Jin Kim, Jinsoo Choi, Tae-Hyun Oh, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
308. Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images
Junsik Kim, Tae-Hyun Oh, Seokju Lee, Fei Pan, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
307. Learning Loss for Active Learning
Donggeun Yoo, In So Kweon
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019 / 07
306. 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
305. 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
304. 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
303. 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
302. 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
301. LinkNet: Relational Embedding for Scene Graph
Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon
Neural Information Processing Systems (NIPS) 2018 / 12
300. CBAM: Convolutional Block Attention Module
Jongchan Park, Sanghyun Woo, Joon-Young Lee, In So Kweon
European Conference on Computer Vision (ECCV) 2018 / 09
299. BAM: Bottleneck Attention Module
Jongchan Park, Sanghyun Woo, Joon-Young Lee, In So Kweon
British Machine Vision Conference (BMVC) 2018 / 09
298. 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
297. 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
296. 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
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