| A review on object pose recovery: From 3D bounding box detectors to full 6D pose estimators C Sahin, G Garcia-Hernando, J Sock, TK Kim Image and Vision Computing 96, 103898, 2020 | 81 | 2020 |
| Pose guided RGBD feature learning for 3D object pose estimation V Balntas, A Doumanoglou, C Sahin, J Sock, R Kouskouridas, TK Kim Proceedings of the IEEE international conference on computer vision, 3856-3864, 2017 | 79 | 2017 |
| Multi-view 6D object pose estimation and camera motion planning using RGBD images J Sock, S Hamidreza Kasaei, L Seabra Lopes, TK Kim Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 63 | 2017 |
| Probabilistic traversability map generation using 3D-LIDAR and camera J Sock, J Kim, J Min, K Kwak 2016 IEEE International Conference on Robotics and Automation (ICRA), 5631-5637, 2016 | 63 | 2016 |
| Indirect correspondence-based robust extrinsic calibration of LiDAR and camera S Sim, J Sock, K Kwak Sensors 16 (6), 933, 2016 | 48 | 2016 |
| Multi-task deep networks for depth-based 6d object pose and joint registration in crowd scenarios J Sock, KI Kim, C Sahin, TK Kim arXiv preprint arXiv:1806.03891, 2018 | 35 | 2018 |
| Perceiving, learning, and recognizing 3d objects: An approach to cognitive service robots S Kasaei, J Sock, LS Lopes, AM Tomé, TK Kim Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 27 | 2018 |
| Instance-and category-level 6d object pose estimation C Sahin, G Garcia-Hernando, J Sock, TK Kim RGB-D Image Analysis and Processing, 243-265, 2019 | 20 | 2019 |
| Introducing pose consistency and warp-alignment for self-supervised 6d object pose estimation in color images J Sock, G Garcia-Hernando, A Armagan, TK Kim 2020 International Conference on 3D Vision (3DV), 291-300, 2020 | 19 | 2020 |
| Active 6d multi-object pose estimation in cluttered scenarios with deep reinforcement learning J Sock, G Garcia-Hernando, TK Kim 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 13 | 2020 |
| Tackling two challenges of 6d object pose estimation: Lack of real annotated rgb images and scalability to number of objects J Sock, P Castro, A Armagan, G Garcia-Hernando, TK Kim arXiv preprint arXiv:2003.12344, 2020 | 5 | 2020 |
| Multi-task deep networks for depth-based 6D object pose and joint registration in crowd scenarios. arXiv 2018 J Sock, KI Kim, C Sahin, TK Kim arXiv preprint arXiv:1806.03891, 0 | 5 | |
| Probabilistic traversability map building for autonomous navigation J Sock, K Kwak, J Min, YW Park 2014 14th International Conference on Control, Automation and Systems (ICCAS …, 2014 | 4 | 2014 |
| Active recognition and domain adaptation for 6D object pose estimation JI Sock Imperial College London, 2021 | | 2021 |
| Multi-Task Learning for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios J Sock, KI Kim, C Sahin, TK Kim Proc. of British Machine Vision Conference (BMVC), 2018 | | 2018 |
| 야지자율주행을 위한 환경인식기술 민지홍， 석주일， 김준， 안성용， 심성대， 곽기호 대한전기학회 학술대회 논문집, 1462-1463, 2016 | | 2016 |
| 영상 다중 분할을 통한 강인한 특징 추출 기반의 차선인식 기법 안성용， 곽기호， 민지홍， 석주일 대한전기학회 학술대회 논문집, 339-340, 2013 | | 2013 |
