Liao Shen (申立奥)

[Arxiv] Generative Photographic Control for Scene-Consistent Video Cinematic Editing
Huiqiang Sun*, Liao Shen*, Zhan Peng, Kun Wang, Size Wu, Yuhang Zang, Tianqi Liu, Zihao Huang, Xingyu Zeng, Zhiguo Cao, Wei Li, Chen Change Loy
[Paper]

Cinectrl is the first video cinematic editing framework that provides fine control over professional camera parameters (e.g., bokeh, shutter speed).

[CVPR 2026] Identity-Preserving Image-to-Video Generation via Reward-Guided Optimization
Liao Shen*, Wentao Jiang*, Yiran Zhu, Jiahe Li, Tiezheng Ge, Zhiguo Cao, Bo Zheng.
[Project page] [Paper] [Code]

IPRO is the first identity-preserving image-to-video generation model via reward feedback learning.

[ICCV 2025] MuGS: Multi-Baseline Generalizable Gaussian Splatting Reconstruction
Yaopeng Lou, Liao Shen, Tianqi Liu, Jiaqi Li, Zihao Huang, Huiqiang Sun, Zhiguo Cao.
[Paper]

MuGS is the first multi-baseline generalizable gaussian splatting method.

[ICCV 2025] Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal Consistency
Tianqi Liu, Zihao Huang, Zhaoxi Chen, Guangcong Wang, Shoukang Hu, Liao Shen, Huiqiang Sun, Zhiguo Cao, Wei Li, Ziwei Liu.
[Project page] [Paper] [Code] [Video]

Free4D is a tuning-free framework for 4D scene generation from a single image or text.

[CVPR 2025] DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splatting
Liao Shen, Tianqi Liu, Huiqiang Sun, Jiaqi Li, Zhiguo Cao, Wei Li, Chen Change Loy.
[Project page] [Paper] [Code]

We introduce DoF-Gaussian, a controllable depth-of-field method for 3D-GS. We develop a lens-based imaging model based on geometric optics principles to control DoF effects. Our framework is customizable and supports various interactive applications.

[ACM MM 2024] Video Bokeh Rendering: Make Casual Videography Cinematic (Best paper candidate)🚀🚀🚀
Yawen Luo, Min Shi, Liao Shen, Yachuan Huang, Zixuan Ye, Juewen Peng, Zhiguo Cao.
[Paper]

We introduce VBR, the video bokeh rendering model that first leverages information from multiple frames to generate refocusable videos from all-in-focus videos.

[ECCV 2024] DreamMover: Leveraging the Prior of Diffusion Models for Image Interpolation with Large Motion
Liao Shen, Tianqi Liu, Huiqiang Sun, Xinyi Ye, Baopu Li, Jianming Zhang, Zhiguo Cao.
[Project page] [Paper] [Code]

By leveraging the prior of diffusion models, DreamMover can generate intermediate images from image pairs with large motion while maintaining semantic consistency.

[ECCV 2024] MVSGaussian: Fast Generalizable Gaussian Splatting Reconstruction from Multi-View Stereo
Tianqi Liu, Guangcong Wang, Shoukang Hu, Liao Shen, Xinyi Ye, Yuhang Zang, Zhiguo Cao, Wei Li, Ziwei Liu.
[Project page] [Paper] [Code]

MVSGaussian is a Gaussian-based method designed for efficient reconstruction of unseen scenes from sparse views in a single forward pass. It offers high-quality initialization for fast training and real-time rendering.

[CVPR 2024] DyBluRF: Dynamic Neural Radiance Fields from Blurry Monocular Video
Huiqiang Sun, Xingyi Li, Liao Shen, Xinyi Ye, Ke Xian, Zhiguo Cao.
[Project page] [Paper] [Code]

DyBluRF is a dynamic neural radiance field method that synthesizes sharp novel views from a monocular video affected by motion blur.

[ACM MM 2023] Make-It-4D: Synthesizing a Consistent Long-Term Dynamic Scene Video from a Single Image
Liao Shen, Xingyi Li, Huiqiang Sun, Juewen Peng, Ke Xian, Zhiguo Cao, Guosheng Lin.
[Paper] [Code]

Make-It-4D is a novel framework that can generate a consistent long-term dynamic video from a single image. The generated video involves both visual content movements and large camera motions, bringing the still image back to life.