暂无分享,去创建一个
Hongyan Liu | Jun He | Jian Xu | Zhicheng Wang | Zhaoxin Fan | Zhengbo Song | Kejian Wu | Hongyan Liu | Jun He | Jason Zhaoxin Fan | Zhicheng Wang | Kejian Wu | Jian Xu | Zhengbo Song | Fan
[1] Cewu Lu,et al. PRIN/SPRIN: On Extracting Point-Wise Rotation Invariant Features , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Ernesto Damiani,et al. Augmented reality technologies, systems and applications , 2010, Multimedia Tools and Applications.
[3] Fuxin Li,et al. PointConv: Deep Convolutional Networks on 3D Point Clouds , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Slobodan Ilic,et al. DPOD: 6D Pose Object Detector and Refiner , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[5] Ronald Azuma,et al. A Survey of Augmented Reality , 1997, Presence: Teleoperators & Virtual Environments.
[6] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[7] Ashutosh Saxena,et al. Robotic Grasping of Novel Objects using Vision , 2008, Int. J. Robotics Res..
[8] Marc Levoy,et al. Efficient variants of the ICP algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.
[9] Ales Leonardis,et al. FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Timothy Patten,et al. Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[12] Hongyan Liu,et al. Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview , 2021, ArXiv.
[13] Dieter Fox,et al. PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes , 2017, Robotics: Science and Systems.
[14] Daniel Cohen-Or,et al. PU-GAN: A Point Cloud Upsampling Adversarial Network , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[15] Ali Etemad,et al. Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting , 2021, European Conference on Computer Vision.
[16] Pascal Fua,et al. Real-Time Seamless Single Shot 6D Object Pose Prediction , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[17] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Wei Sun,et al. PVN3D: A Deep Point-Wise 3D Keypoints Voting Network for 6DoF Pose Estimation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Gim Hee Lee,et al. Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation , 2020, ECCV.
[20] Haoqiang Fan,et al. FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Yue Wang,et al. Dynamic Graph CNN for Learning on Point Clouds , 2018, ACM Trans. Graph..
[22] J. Kumar,et al. Recent Development of Augmented Reality in Surgery: A Review , 2017, Journal of healthcare engineering.
[23] Ali Farhadi,et al. YOLOv3: An Incremental Improvement , 2018, ArXiv.
[24] Hongyan Liu,et al. Attentive Rotation Invariant Convolution for Point Cloud-based Large Scale Place Recognition , 2021, ArXiv.
[25] Jonathan T. Barron,et al. iNeRF: Inverting Neural Radiance Fields for Pose Estimation , 2020, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[26] Leonidas J. Guibas,et al. Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Ruigang Yang,et al. ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Xiangyang Ji,et al. CDPN: Coordinates-Based Disentangled Pose Network for Real-Time RGB-Based 6-DoF Object Pose Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[29] Jiaru Song,et al. HybridPose: 6D Object Pose Estimation Under Hybrid Representations , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Nassir Navab,et al. SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[31] Tae-Kyun Kim,et al. Introducing Pose Consistency and Warp-Alignment for Self-Supervised 6D Object Pose Estimation in Color Images , 2020, 2020 International Conference on 3D Vision (3DV).
[32] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[33] Bo Dai,et al. Unsupervised 3D Shape Completion through GAN Inversion , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Kai Xu,et al. Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Yi Li,et al. DeepIM: Deep Iterative Matching for 6D Pose Estimation , 2018, International Journal of Computer Vision.
[36] Chi-Keung Tang,et al. GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision , 2020, ECCV.
[37] Nassir Navab,et al. Deep Model-Based 6D Pose Refinement in RGB , 2018, ECCV.
[38] Kui Jia,et al. DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[39] Byeong-Uk Lee,et al. Category-Level Metric Scale Object Shape and Pose Estimation , 2021, IEEE Robotics and Automation Letters.
[40] Ross B. Girshick,et al. Mask R-CNN , 2017, 1703.06870.
[41] Yang Yu,et al. Unsupervised Representation Learning with Deep Convolutional Neural Network for Remote Sensing Images , 2017, ICIG.
[42] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[43] Vijay Kumar,et al. Robotic grasping and contact: a review , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).
[44] Wenqiang Zhang,et al. EfficientPose: Efficient human pose estimation with neural architecture search , 2020, Computational Visual Media.
[45] Harshad Rai,et al. Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks , 2018 .
[46] S. Umeyama,et al. Least-Squares Estimation of Transformation Parameters Between Two Point Patterns , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[47] Xiaogang Wang,et al. Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Michael J. Black,et al. VIBE: Video Inference for Human Body Pose and Shape Estimation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[49] Timo Aila,et al. A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[50] Ming-Yu Liu,et al. Coupled Generative Adversarial Networks , 2016, NIPS.
[51] Hujun Bao,et al. PVNet: Pixel-Wise Voting Network for 6DoF Pose Estimation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[52] Dieter Fox,et al. Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects , 2018, CoRL.
[53] Dragomir Anguelov,et al. Scalability in Perception for Autonomous Driving: Waymo Open Dataset , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).