
NVIDIA Research is passionate about developing the technology and finding the breakthroughs that bring positive change to the world.
重点功能或内容:
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BibTeX格式的引用:为学术研究提供BibTeX格式的引用参考。
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PDF文档:链接到各个研究的PDF文档或arXiv版本。
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研究成果:包含多个研究项目,如DIBR++、StyleGAN-NADA等。
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研究团队和人员:展示了多位研究人员的贡献,包括Jun Gao、Tianchang Shen、Zian Wang等。
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开源代码:提供了相关研究的代码链接。
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研究论文:提供了相关研究的详细论文信息和链接。
主要研究项目
| 项目名称 | 相关会议 | 描述 |
|---|---|---|
| Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis | NeurIPS 2021 | 提出了高分辨率3D形状合成的新方法。 |
| Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering | SIGGRAPH Asia 2020 | 提供了高性能可微分渲染的模块化工具。 |
| Learning Deformable Tetrahedral Meshes for 3D Reconstruction | NeurIPS 2020 | 提出了变形四面体网格用于3D重建。 |
| DIBR++ | NeurIPS 2020 | 研究3D重建领域中的新方法。 |
| DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer | NeurIPS 2021 | 提出了新的渲染技术,用于预测光照和材质。 |
| EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks | CVPR 2022 | 提出了高效的几何感知生成对抗网络。 |
| StyleGAN-NADA | CVPR 2022 | 提出了新型生成对抗网络架构,优化了3D形状合成。 |
盾灵安全导航
At NVIDIA, you’ll solve some of the world’s hardest problems and discover new ways to improve the quality of life for people everywhere. From healthcare to robots, self-driving cars to blockbuster movies—and a growing list of opportunities every single day—explore all of our open roles, including internships and new college graduate positions.
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