Robotics and Computer Vision Lab

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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
665. Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation
Sungsu Hur, Inkyu Shin, Kwanyong Park, Sanghyun Woo, In So Kweon
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023 / 01
664. Self-supervised Monocular Depth Estimation from Thermal Images via Adversarial Multi-spectral Adaptation
Ukcheol Shin, Kwanyong Park, Byeong-Uk Lee, Kyunghyun Lee, In So Kweon
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023 / 01
663. Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition
Youngjoon Jang, Youngtaek Oh, Jae Won Cho, Dong-Jin Kim, Joon Son Chung, In So Kweon
British Machine Vision Conference (BMVC) 2022 / 11
662. Lightweight Depth Completion Network with Local Similarity-Preserving Knowledge Distillation
Yongseop Jeong, Jinsun Park, Donghyeon Cho, Yoonjin Hwang, Seibum Choi and In So Kweon
Sensors 2022 / 09
661. Self-supervised Monocular Depth and Motion Learning in Dynamic Scenes: Semantic Prior to Rescue
Seokju Lee, Francois Rameau, Sunghoon Im, In So Kweon
International Journal of Computer Vision (IJCV) 2022 / 07
660. PointMixer: MLP-Mixer for Point Cloud Understanding
Jaesung Choe*, Chunghyun Park*, Francois Rameau, Jaesik Park, In So Kweon
European Conference on Computer Vision (ECCV) 2022 / 10
659. Facial Depth and Normal Estimation using Single Dual-Pixel Camera
Minjun Kang, Jaesung Choe, Hyowon Ha, Hae-Gon Jeon, Sunghoon Im, In So Kweon, Kuk-Jin Yoon
European Conference on Computer Vision (ECCV) 2022 / 10
658. Fast Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Chaoning Zhang, Kang Zhang, Chenshuang Zhang, Axi Niu, Jiu Feng, Chang D. Yoo, In So Kweon
European Conference on Computer Vision (ECCV) 2022 / 10
657. ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound Domain Adaptation in Semantic Segmentation
Fei Pan, Sungsu Hur, Seokju Lee, Junsik Kim, In So Kweon
European Conference on Computer Vision (ECCV) 2022 / 10
656. A Unified Learning Framework for Large Vocabulary Video Object Detection
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh, In So Kweon, Joon-Young Lee
European Conference on Computer Vision (ECCV) 2022 / 10
655. Tracking by Associating Clips
Sanghyun Woo, Kwanyong Park, Seoung Wug Oh, In So Kweon, Joon-Young Lee
European Conference on Computer Vision (ECCV) 2022 / 10
654. The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing
Dawit Mureja Argaw, Fabian Caba Heilbron, Markus Woodson, Joon-Young Lee, In So Kweon
European Conference on Computer Vision 2022 / 10
653. DRL-ISP: Multi-Objective Camera ISP with Deep Reinforcement Learning
Ukcheol Shin, Kyunghyun Lee, In So Kweon
International Conference on Intelligent Robots and Systems (IROS) 2022 / 06
652. Maximizing Self-supervision from Thermal Image for Effective Self-supervised Learning of Depth and Ego-motion
Ukcheol Shin, Kyunghyun Lee, Byeong-Uk Lee, In So Kweon
IEEE Robotics and Automation Letters (RA-L) 2022 / 06
651. Self-supervised Depth and Ego-motion Estimation for Monocular Thermal Video using Multi-spectral Consistency Loss
Ukcheol Shin, Kyunghyun Lee, Seokju Lee, In So Kweon
IEEE Robotics and Automation Letters (RA-L) 2022 / 04
650. Identification of Vehicle Dynamics Model and Lever-arm for Arbitrarily Mounted Motion Sensor
Yoonjin Hwang, Yongseop Jeong, In So Kweon, Seibum Choi
IEEE Sensors 2021 / 12
649. Investigating Top-k White-Box and Transferable Black-box Attack
Chaoning Zhang, Philip Benz, Adil Karjauv, JaeWon Cho, Kang Zhang, In So Kweon
Computer Vision and Pattern Recognition, CVPR 2022 / 03
648. DASO: Distribution-Aware Semantics-Oriented Pseudo-Label for Imbalanced Semi-Supervised Learning
Youngtaek Oh, Dong-Jin Kim, and In So Kweon
Computer Vision and Pattern Recognition, CVPR 2022 / 03
647. Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo
Chaoning Zhang*, Kang Zhang,∗, Trung X. Pham,∗, Axi Niu, Zhinan Qiao Chang D. Yoo, In So Kweon
Computer Vision and Pattern Recognition, CVPR 2022 / 03
646. TubeFormer-DeepLab: Video Mask Transformer
Dahun Kim, Jun Xie, Huiyu Wang, Siyuan Qiao, Qihang Yu, Hong-Seok Kim,Hartwig Adam, In So Kweon, Liang-Chieh Chen
Computer Vision and Pattern Recognition, CVPR 2022 / 03
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