Baorui Ma

Orcid: 0000-0002-7229-2386

According to our database1, Baorui Ma authored at least 20 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
CAP-UDF: Learning Unsigned Distance Functions Progressively From Raw Point Clouds With Consistency-Aware Field Optimization.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Fast Learning of Signed Distance Functions From Noisy Point Clouds via Noise to Noise Mapping.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

TV-3DG: Mastering Text-to-3D Customized Generation with Visual Prompt.
CoRR, 2024

Inferring 3D Occupancy Fields through Implicit Reasoning on Silhouette Images.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

3D-OAE: Occlusion Auto-Encoders for Self-Supervised Learning on Point Clouds.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Uni3D: Exploring Unified 3D Representation at Scale.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

UDiFF: Generating Conditional Unsigned Distance Fields with Optimal Wavelet Diffusion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Learning Continuous Implicit Field with Local Distance Indicator for Arbitrary-Scale Point Cloud Upsampling.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation.
CoRR, 2023

Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping.
Proceedings of the International Conference on Machine Learning, 2023

Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Towards Better Gradient Consistency for Neural Signed Distance Functions via Level Set Alignment.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NeAF: Learning Neural Angle Fields for Point Normal Estimation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Surface Reconstruction from Point Clouds by Learning Predictive Context Priors.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Reconstructing 3D Shapes From Multiple Sketches Using Direct Shape Optimization.
IEEE Trans. Image Process., 2020

Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces.
CoRR, 2020


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