PREDATOR: Registration of 3D Point Clouds with Low Overlap S Huang, Z Gojcic, M Usvyatsov, A Wieser, K Schindler IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2020 | 560 | 2020 |
The perfect match: 3d point cloud matching with smoothed densities Z Gojcic, C Zhou, JD Wegner, A Wieser IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), 5545 …, 2019 | 543 | 2019 |
LION: Latent Point Diffusion Models for 3D Shape Generation X Zeng, A Vahdat, F Williams, Z Gojcic, O Litany, S Fidler, K Kreis Neural Information Processing Systems (NeurIPS), 2022 | 427* | 2022 |
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images J Gao, T Shen, Z Wang, W Chen, K Yin, D Li, O Litany, Z Gojcic, S Fidler Neural Information Processing Systems (NeurIPS), 2022 | 424 | 2022 |
Learning multiview 3D point cloud registration Z Gojcic, C Zhou, JD Wegner, LJ Guibas, T Birdal IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), 2020 | 211 | 2020 |
Weakly Supervised Learning of Rigid 3D Scene Flow Z Gojcic, O Litany, A Wieser, LJ Guibas, T Birdal IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2021 | 110 | 2021 |
CaSPR: Learning canonical spatiotemporal point cloud representations D Rempe, T Birdal, Y Zhao, Z Gojcic, S Sridhar, LJ Guibas Neural Information Processing Systems (NeurIPS 2020), 2020 | 76 | 2020 |
Flexible Isosurface Extraction for Gradient-Based Mesh Optimization. T Shen, J Munkberg, J Hasselgren, K Yin, Z Wang, W Chen, Z Gojcic, ... ACM Trans. Graph. 42 (4), 37:1-37:16, 2023 | 73 | 2023 |
Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes Z Wang, T Shen, J Gao, S Huang, J Munkberg, J Hasselgren, Z Gojcic, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2023), 2023 | 68 | 2023 |
Neural fields as learnable kernels for 3d reconstruction F Williams, Z Gojcic, S Khamis, D Zorin, J Bruna, S Fidler, O Litany Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 65 | 2022 |
Neural Kernel Surface Reconstruction J Huang, Z Gojcic, M Atzmon, O Litany, S Fidler, F Williams IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4369-4379, 2023 | 57 | 2023 |
Adaptive Shells for Efficient Neural Radiance Field Rendering Z Wang, T Shen, M Nimier-David, N Sharp, J Gao, A Keller, S Fidler, ... ACM Transactions on Graphics (SIGGRAPH Asia) 42 (6), 2023 | 48 | 2023 |
Dynamic 3D Scene Analysis by Point Cloud Accumulation S Huang, Z Gojcic, J Huang, A Wieser, K Schindler European Conference on Computer Vision (ECCV), 2022 | 48 | 2022 |
Neural LiDAR Fields for Novel View Synthesis S Huang, Z Gojcic, Z Wang, F Williams, Y Kasten, S Fidler, K Schindler, ... IEEE International Conference on Computer Vision (ICCV), 2023, 2023 | 44 | 2023 |
Multiway non-rigid point cloud registration via learned functional map synchronization J Huang, T Birdal, Z Gojcic, LJ Guibas, SM Hu IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 2038-2053, 2022 | 39 | 2022 |
Dense 3D displacement vector fields for point cloud-based landslide monitoring Z Gojcic, L Schmid, A Wieser Landslides 18, 3821-3832, 2021 | 39 | 2021 |
F2S3: Robustified determination of 3D displacement vector fields using deep learning Z Gojcic, C Zhou, A Wieser Journal of Applied Geodesy 14 (2), 177-189, 2020 | 25 | 2020 |
Learned compact local feature descriptor for TLS-based geodetic monitoring of natural outdoor scenes Z Gojcic, C Zhou, A Wieser International Annals of the Photogrammetry, Remote Sensing and Spatial …, 2018 | 22 | 2018 |
Or Litany, Sanja Fidler, and Karsten Kreis X Zeng, A Vahdat, F Williams, Z Gojcic Lion: Latent point diffusion models for 3d shape generation 4, 2022 | 20 | 2022 |
The potential of point clouds for the analysis of rock kinematics in large slope instabilities: examples from the Swiss Alps: Brinzauls, Pizzo Cengalo and Spitze Stei R Kenner, V Gischig, Z Gojcic, Y Quéau, C Kienholz, D Figi, R Thöny, ... Landslides 19 (6), 1357-1377, 2022 | 15 | 2022 |