| Neural-pull: Learning signed distance functions from point clouds by learning to pull space onto surfaces B Ma, Z Han, YS Liu, M Zwicker arXiv preprint arXiv:2011.13495, 2020 | 166 | 2020 |
| Surface reconstruction from point clouds by learning predictive context priors B Ma, YS Liu, M Zwicker, Z Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 86 | 2022 |
| Learning consistency-aware unsigned distance functions progressively from raw point clouds J Zhou, B Ma, YS Liu, Y Fang, Z Han Advances in Neural Information Processing Systems 35, 16481-16494, 2022 | 79 | 2022 |
| Reconstructing surfaces for sparse point clouds with on-surface priors B Ma, YS Liu, Z Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 75 | 2022 |
| Uni3d: Exploring unified 3d representation at scale J Zhou, J Wang, B Ma, YS Liu, T Huang, X Wang arXiv preprint arXiv:2310.06773, 2023 | 74 | 2023 |
| Reconstructing 3D shapes from multiple sketches using direct shape optimization Z Han, B Ma, YS Liu, M Zwicker IEEE Transactions on Image Processing 29, 8721-8734, 2020 | 55 | 2020 |
| Towards better gradient consistency for neural signed distance functions via level set alignment B Ma, J Zhou, YS Liu, Z Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 44 | 2023 |
| Neaf: Learning neural angle fields for point normal estimation S Li, J Zhou, B Ma, YS Liu, Z Han Proceedings of the AAAI conference on artificial intelligence 37 (1), 1396-1404, 2023 | 43 | 2023 |
| Learning a more continuous zero level set in unsigned distance fields through level set projection J Zhou, B Ma, S Li, YS Liu, Z Han Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 29 | 2023 |
| Learning signed distance functions from noisy 3d point clouds via noise to noise mapping B Ma, YS Liu, Z Han | 24 | 2023 |
| Differentiable registration of images and lidar point clouds with voxelpoint-to-pixel matching J Zhou, B Ma, W Zhang, Y Fang, YS Liu, Z Han Advances in Neural Information Processing Systems 36, 51166-51177, 2023 | 21 | 2023 |
| Geodream: Disentangling 2d and geometric priors for high-fidelity and consistent 3d generation B Ma, H Deng, J Zhou, YS Liu, T Huang, X Wang arXiv preprint arXiv:2311.17971, 2023 | 20 | 2023 |
| 3d-oae: Occlusion auto-encoders for self-supervised learning on point clouds J Zhou, X Wen, B Ma, YS Liu, Y Gao, Y Fang, Z Han 2024 IEEE International Conference on Robotics and Automation (ICRA), 15416 …, 2024 | 19 | 2024 |
| Learning continuous implicit field with local distance indicator for arbitrary-scale point cloud upsampling S Li, J Zhou, B Ma, YS Liu, Z Han Proceedings of the AAAI Conference on Artificial Intelligence 38 (4), 3181-3189, 2024 | 16 | 2024 |
| Self-supervised point cloud representation learning with occlusion auto-encoder J Zhou, X Wen, B Ma, YS Liu, Y Fang, Z Han arXiv e-prints, arXiv: 2203.14084, 2022 | 12 | 2022 |
| Udiff: Generating conditional unsigned distance fields with optimal wavelet diffusion J Zhou, W Zhang, B Ma, K Shi, YS Liu, Z Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 11 | 2024 |
| CAP-UDF: Learning Unsigned Distance Functions Progressively from Raw Point Clouds with Consistency-Aware Field Optimization J Zhou, B Ma, S Li, YS Liu, Y Fang, Z Han IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 9 | 2024 |
| Fast Learning of Signed Distance Functions From Noisy Point Clouds Via Noise to Noise Mapping YSL Junsheng Zhou, Baorui Ma IEEE transactions on pattern analysis and machine intelligence, 2024 | 5 | 2024 |
| Inferring 3D occupancy fields through implicit reasoning on silhouette images B Ma, YS Liu, M Zwicker, Z Han Proceedings of the 32nd ACM International Conference on Multimedia, 10248-10257, 2024 | 1 | 2024 |
| BLCC: A Benchmark for Multi-LiDAR and Multi-camera Calibration M Hou, G Wang, Z Wang, T Zhang, B Ma International Conference on Multimedia Modeling, 139-152, 2025 | | 2025 |
