Sheng Miao (苗升)

I am currently pursuing my Ph.D. at Zhejiang University, under the guidance of Prof. Yiyi Liao. Prior to this, I completed my Master's degree in Control Science and Engineering at Northwestern Polytechnical University (NWPU), advised by Prof. Xiaoxiong Liu. I received the Bachelor's degree from NWPU in 2019.

Currently, I have focused on projects involving feed-forward techniques for 3D/4D scene reconstruction and 3D generation. I serve as the conference reviewer of CVPR and NIPS.

I am looking for a full-time job in the field of 3D/4D scene reconstruction and 3D generation. Feel free to contact me at shengmiao@zju.edu.cn.

Email / Github

News

Jun 26, 2025: One paper is accepted to ICCV 2025.
Feb 27, 2025: One paper is accepted to CVPR 2025.
Jul 1, 2024: One paper is accepted to ECCV 2024.

Selected Publications

* means equal contribution.

	Vivid4D: Improving 4D Reconstruction from Monocular Video by Video Inpainting Jiaxin Huang, Sheng Miao, Bangbang Yang, Yuewen Ma, Yiyi Liao, ICCV, 2025 project page / arXiv A generative framework that addresses the challenge of reconstructing dynamic scenes from casual monocular videos with video diffusion model.
	EVolSplat: Efficient Volume-based Gaussian Splatting for Urban View Synthesis Sheng Miao, Jiaxin Huang, Dongfeng Bai, Xu Yan, Hongyu Zhou, Yue Wang, Bingbing Liu, Andreas Geiger, Yiyi Liao, CVPR, 2025 project page / arXiv A generalizable framework that predicts 3D Gaussians across multiple frames within a unified volume using convolutional networks.
	Efficient Depth-Guided Urban View Synthesis Sheng Miao^∗, Jiaxin Huang^∗, Dongfeng Bai, Weichao Qiu, Bingbing Liu, Andreas Geiger, Yiyi Liao, ECCV, 2024 project page / arXiv A generalizable NeRF model that explicitly leverages geometric priors for feed-forward inference on unbounded sparse urban scenes.
	A Visual SLAM Robust against Dynamic Objects Based on Hybrid Semantic-Geometry Information Sheng Miao, Xiaoxiong Liu, Dazheng Wei, Changze Li, ISPRS International Journal of Geo-Information, 2021, SCI Journal A method for static/dynamic image segmentation that leverages semantic and geometric modules, including optical flow residual clustering, epipolar constraint checks, semantic segmentation to tackle dynamics.