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2020 – today
- 2025
[j3]Yifan Wang
, Fei Yang, Luka Murn, Juil Sock, Marc Górriz Blanch, Shuai Wan, Wei Zhang, Fuzheng Yang, Luis Herranz:
Enhanced neural video compression for cloud gaming videos with aligned frame generation. Expert Syst. Appl. 261: 125535 (2025)- 2021
- [b1]Juil Sock:
Active recognition and domain adaptation for 6D object pose estimation. Imperial College London, UK, 2021 - 2020
- [j2]Caner Sahin, Guillermo Garcia-Hernando, Juil Sock, Tae-Kyun Kim:
A review on object pose recovery: From 3D bounding box detectors to full 6D pose estimators. Image Vis. Comput. 96: 103898 (2020) - [c7]Juil Sock, Guillermo Garcia-Hernando, Anil Armagan, Tae-Kyun Kim:
Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images. 3DV 2020: 291-300 - [c6]Juil Sock, Guillermo Garcia-Hernando, Tae-Kyun Kim:
Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning. IROS 2020: 10564-10571 - [i5]Caner Sahin, Guillermo Garcia-Hernando, Juil Sock, Tae-Kyun Kim:
A Review on Object Pose Recovery: from 3D Bounding Box Detectors to Full 6D Pose Estimators. CoRR abs/2001.10609 (2020) - [i4]Juil Sock, Pedro Castro, Anil Armagan, Guillermo Garcia-Hernando, Tae-Kyun Kim:
Tackling Two Challenges of 6D Object Pose Estimation: Lack of Real Annotated RGB Images and Scalability to Number of Objects. CoRR abs/2003.12344 (2020)
2010 – 2019
- 2019
- [i3]Caner Sahin, Guillermo Garcia-Hernando, Juil Sock, Tae-Kyun Kim:
Instance- and Category-level 6D Object Pose Estimation. CoRR abs/1903.04229 (2019) - [i2]Juil Sock, Guillermo Garcia-Hernando, Tae-Kyun Kim:
Active 6D Multi-Object Pose Estimation in Cluttered Scenarios with Deep Reinforcement Learning. CoRR abs/1910.08811 (2019) - 2018
- [c5]S. Hamidreza Kasaei, Juil Sock, Luís Seabra Lopes, Ana Maria Tomé, Tae-Kyun Kim:
Perceiving, Learning, and Recognizing 3D Objects: An Approach to Cognitive Service Robots. AAAI 2018: 596-603 - [c4]Juil Sock, Kwang In Kim, Caner Sahin, Tae-Kyun Kim:
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios. BMVC 2018: 90 - [i1]Juil Sock, Kwang In Kim, Caner Sahin, Tae-Kyun Kim:
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios. CoRR abs/1806.03891 (2018) - 2017
- [c3]Vassileios Balntas, Andreas Doumanoglou, Caner Sahin, Juil Sock, Rigas Kouskouridas, Tae-Kyun Kim:
Pose Guided RGBD Feature Learning for 3D Object Pose Estimation. ICCV 2017: 3876-3884 - [c2]Juil Sock, S. Hamidreza Kasaei, Luís Seabra Lopes, Tae-Kyun Kim:
Multi-view 6D Object Pose Estimation and Camera Motion Planning Using RGBD Images. ICCV Workshops 2017: 2228-2235 - 2016
- [j1]Sungdae Sim, Juil Sock, Kiho Kwak:
Indirect Correspondence-Based Robust Extrinsic Calibration of LiDAR and Camera. Sensors 16(6): 933 (2016) - [c1]Juil Sock, Jun Kim, Jihong Min, Kiho Kwak:
Probabilistic traversability map generation using 3D-LIDAR and camera. ICRA 2016: 5631-5637
Coauthor Index
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