| Shrec16 track: largescale 3d shape retrieval from shapenet core55 M Savva, F Yu, H Su, M Aono, B Chen, D Cohen-Or, W Deng, H Su, S Bai, ... Proceedings of the eurographics workshop on 3D object retrieval 10, 13, 2016 | 167 | 2016 |
| Structure-slam: Low-drift monocular slam in indoor environments Y Li, N Brasch, Y Wang, N Navab, F Tombari IEEE Robotics and Automation Letters 5 (4), 6583-6590, 2020 | 122 | 2020 |
| Softpoolnet: Shape descriptor for point cloud completion and classification Y Wang, DJ Tan, N Navab, F Tombari Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 86 | 2020 |
| Forknet: Multi-branch volumetric semantic completion from a single depth image Y Wang, DJ Tan, N Navab, F Tombari Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 73 | 2019 |
| Learning local displacements for point cloud completion Y Wang, DJ Tan, N Navab, F Tombari Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 49 | 2022 |
| Legoformer: Transformers for block-by-block multi-view 3d reconstruction F Yagubbayli, Y Wang, A Tonioni, F Tombari arXiv preprint arXiv:2106.12102, 2021 | 39 | 2021 |
| Adversarial semantic scene completion from a single depth image Y Wang, DJ Tan, N Navab, F Tombari 2018 International Conference on 3D Vision (3DV), 426-434, 2018 | 37 | 2018 |
| Softpool++: An encoder–decoder network for point cloud completion Y Wang, DJ Tan, N Navab, F Tombari International Journal of Computer Vision 130 (5), 1145-1164, 2022 | 21 | 2022 |
| Lidar upsampling with sliced wasserstein distance A Savkin, Y Wang, S Wirkert, N Navab, F Tombari IEEE Robotics and Automation Letters 8 (1), 392-399, 2022 | 14 | 2022 |
| Variational object-aware 3-d hand pose from a single rgb image Y Gao, Y Wang, P Falco, N Navab, F Tombari IEEE Robotics and Automation Letters 4 (4), 4239-4246, 2019 | 14 | 2019 |
| From 2D to 3D: Re-thinking benchmarking of monocular depth prediction EP Örnek, S Mudgal, J Wald, Y Wang, N Navab, F Tombari arXiv preprint arXiv:2203.08122, 2022 | 12 | 2022 |
| Self-restraint object recognition by model based CNN learning Y Wang, W Deng 2016 IEEE International Conference on Image Processing (ICIP), 654-658, 2016 | 12 | 2016 |
| Generative model with coordinate metric learning for object recognition based on 3D models Y Wang, W Deng IEEE Transactions on Image Processing 27 (12), 5813-5826, 2018 | 9 | 2018 |
| Zigzagnet: Efficient deep learning for real object recognition based on 3d models Y Wang, C Cui, X Zhou, W Deng Computer Vision–ACCV 2016: 13th Asian Conference on Computer Vision, Taipei …, 2017 | 3 | 2017 |
| Drivedreamer4d: World models are effective data machines for 4d driving scene representation G Zhao, C Ni, X Wang, Z Zhu, X Zhang, Y Wang, G Huang, X Chen, ... arXiv preprint arXiv:2410.13571, 2024 | 2 | 2024 |
| Raneus: Ray-adaptive neural surface reconstruction Y Wang, DJ Tan, N Navab, F Tombari 2024 International Conference on 3D Vision (3DV), 53-63, 2024 | 2 | 2024 |
| Self-Supervised Latent Space Optimization With Nebula Variational Coding Y Wang, DJ Tan, N Navab, F Tombari IEEE Transactions on Pattern Analysis and Machine Intelligence 46 (3), 1397-1411, 2022 | 1 | 2022 |
| Training-free Regional Prompting for Diffusion Transformers A Chen, J Xu, W Zheng, G Dai, Y Wang, R Zhang, H Wang, S Zhang arXiv preprint arXiv:2411.02395, 2024 | | 2024 |
| MVGS: Multi-view-regulated Gaussian Splatting for Novel View Synthesis X Du, Y Wang, X Yu arXiv preprint arXiv:2410.02103, 2024 | | 2024 |
| High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces B Huang, Y Wang, A Nguyen, D Elson, F Vasconcelos, D Stoyanov arXiv preprint arXiv:2404.13437, 2024 | | 2024 |
Federico TombariGoogle, TU MunichVerified email at in.tum.de
