Robotics and Computer Vision Lab

Publications

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저 자 Seong-Heum Kim, Gyeongmin Choe, Byungtae Ahn, In So Kweon
학 회 IEEE International Conference on Robotics and Automation (ICRA)
Notes This research was supported by the Ministry of Trade, Industry & Energy and the Korea Evaluation Institute of Industrial Technology (KEIT) with the program number of "10060110". The first author sincerely appreciates Prof. Sung-eui Yoon at KAIST for valuable discussions.
논문일시(Year) 2017
논문일시(Month) 05
In this paper, we present a visual learning framework to retrieve a 3D model and estimate its pose from a single image. To increase the quantity and quality of training data, we define our simulation space in the near infrared (NIR) band, and utilize quasi-Monte Carlo (MC) method for scalable photorealistic rendering of manufactured components. Two types of Convolutional Neural Networks (CNNs) architectures are trained over these synthetic data and relatively small amount of real data. The first CNN model seeks the most discriminative information to classify industrial components with fine-grained shape attributes. Once a 3D model is identified, one of the category-specific CNNs is tested for pose regression in the second phase. The mixed data for learning object categories is useful in domain adaptation and attention mechanism in our system. We validate our data-driven method with 88 component models, including one practical product, and the experimental results are qualitatively demonstrated. Also, the CNNs trained with various conditions of mixed data are quantitatively analyzed to discuss this approach.

List of Articles
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
295. 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
294. 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
293. 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
292. 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
291. 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
290. 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
289. 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
288. 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
287. 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
286. 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
285. 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
284. 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
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