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I am currently a fourth-year Ph.D student in School of Software, Tsinghua University, advised by Prof. Yu-Shen Liu. I got my bachelor's degree from School of Software, Tsinghua University in 2021. My research interests lie in the area of 3D computer vision and grapics, especially in multi-view neural rendering, 3D reconstruction and scene understanding. |
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(* Equal Contribution) |
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Wenyuan Zhang, Yu-Shen Liu, Zhizhong Han Advances in Neural Information Processing Systems (NeurIPS), 2024 project page | arXiv We propose a method that seamlessly merge 3DGS with the learning of neural SDFs. To this end, we dynamically align 3D Gaussians on the zero-level set of the neural SDF. Meanwhile, we update the neural SDF by pulling neighboring space to the pulled 3D Gaussians, which progressively refine the signed distance field near the surface. |
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Wenyuan Zhang, Kanle Shi, Yu-Shen Liu, Zhizhong Han European Conference on Computer Vision (ECCV), 2024 project page | arXiv | code We present a novel differentiable renderer to infer UDFs from multi-view images. Instead of using hand-crafted equations, our differentiable renderer is a neural network which is pre-trained in a data-driven manner, dubbed volume rendering priors. |
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Junsheng Zhou*, Baorui Ma*, Wenyuan Zhang, Yi Fang, Yu-Shen Liu, Zhizhong Han Conference on Neural Information Processing Systems (NeurIPS), 2023 (Spotlight) arXiv | code We design a triplet network to learn VoxelPoint-to-Pixel matching via a differentiable probabilistic PnP solver. |
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Wenyuan Zhang, Ruofan Xing, Yunfan Zeng, Yu-Shen Liu, Kanle Shi, Zhizhong Han IEEE Transactions on Image Processing (TIP), 2023 project page | arXiv | code We introduce a general strategy to speed up the learning procedure for almost all radiance fields based methods. The key idea is to reduce the redundancy by shooting much fewer rays in the multi-view volume rendering procedure. |
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