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Shenzhou Chen

3 accepted papers

2024

"NeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generation"

ECCV 2024poster

"3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isolation without considering spatial consistency. As a result, these approaches ex…

2024

LAM3D: Large Image-Point Clouds Alignment Model for 3D Reconstruction from Single Image

NeurIPS 2024poster

Large Reconstruction Models have made significant strides in the realm of automated 3D content generation from single or multiple input images. Despite their success, these models often produce 3D meshes with geometric inaccuracies, stemming from the inherent challenges of deducing 3D shapes solely…

Cited by 3SourcePDFScholar
2021

A Multi-spectral Dataset for Evaluating Motion Estimation Systems

ICRA 2021poster

Visible images have been widely used for motion estimation. Thermal images, in contrast, are more challenging to be used in motion estimation since they typically have lower resolution, less texture, and more noise. In this paper, a novel dataset for evaluating the performance of multi-spectral moti…

Cited by 17SourcecodeScholar