Zan Gojcic

Orcid: 0000-0001-6392-2158

According to our database1, Zan Gojcic authored at least 18 papers between 2019 and 2023.

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Bibliography

2023
Adaptive Shells for Efficient Neural Radiance Field Rendering.
ACM Trans. Graph., December, 2023

Flexible Isosurface Extraction for Gradient-Based Mesh Optimization.
ACM Trans. Graph., August, 2023

Multiway Non-Rigid Point Cloud Registration via Learned Functional Map Synchronization.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Neural Fields meet Explicit Geometric Representation for Inverse Rendering of Urban Scenes.
CoRR, 2023

Towards Viewpoint Robustness in Bird's Eye View Segmentation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neural LiDAR Fields for Novel View Synthesis.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neural Fields Meet Explicit Geometric Representations for Inverse Rendering of Urban Scenes.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Neural Kernel Surface Reconstruction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
LION: Latent Point Diffusion Models for 3D Shape Generation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Dynamic 3D Scene Analysis by Point Cloud Accumulation.
Proceedings of the Computer Vision - ECCV 2022, 2022

Neural Fields as Learnable Kernels for 3D Reconstruction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Benefiting from local rigidity in 3D point cloud processing.
PhD thesis, 2021

Predator: Registration of 3D Point Clouds With Low Overlap.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Weakly Supervised Learning of Rigid 3D Scene Flow.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
CaSPR: Learning Canonical Spatiotemporal Point Cloud Representations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Multiview 3D Point Cloud Registration.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
The Perfect Match: 3D Point Cloud Matching With Smoothed Densities.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019


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