4 citations · 5 across the 13 of their papers we have counts for
14 papers · 1 filter
Relit-LiVE: Relight Video by Jointly Learning Environment Video
Weiqing Xiao, Hong Li, Xiuyu Yang +7
Recent advances have shown that large-scale video diffusion models can be repurposed as neural renderers by first decomposing videos into intrinsic scene representations and then p…
ArtHOI: Articulated Human-Object Interaction Synthesis by 4D Reconstruction from Video Priors
Zihao Huang, Tianqi Liu, Zhaoxi Chen +7
Synthesizing physically plausible articulated human-object interactions (HOI) without 3D/4D supervision remains a fundamental challenge. While recent zero-shot approaches leverage…
Light-X: Generative 4D Video Rendering with Camera and Illumination Control
Tianqi Liu, Zhaoxi Chen, Zihao Huang +8
Recent advances in illumination control extend image-based methods to video, yet still facing a trade-off between lighting fidelity and temporal consistency. Moving beyond relighti…
Generative Photographic Control for Scene-Consistent Video Cinematic Editing
Huiqiang Sun, Liao Shen, Zhan Peng +9
Cinematic storytelling is profoundly shaped by the artful manipulation of photographic elements such as depth of field and exposure. These effects are crucial in conveying mood and…
4DNeX: Feed-Forward 4D Generative Modeling Made Easy
Zhaoxi Chen, Tianqi Liu, Long Zhuo +6
We present 4DNeX, the first feed-forward framework for generating 4D (i.e., dynamic 3D) scene representations from a single image. In contrast to existing methods that rely on comp…
MuGS: Multi-Baseline Generalizable Gaussian Splatting Reconstruction
Yaopeng Lou, Liao Shen, Tianqi Liu +4
We present Multi-Baseline Gaussian Splatting (MuGS), a generalized feed-forward approach for novel view synthesis that effectively handles diverse baseline settings, including spar…
Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal Consistency
Tianqi Liu, Zihao Huang, Zhaoxi Chen +7
We present Free4D, a novel tuning-free framework for 4D scene generation from a single image. Existing methods either focus on object-level generation, making scene-level generatio…
DoF-Gaussian: Controllable Depth-of-Field for 3D Gaussian Splatting
Liao Shen, Tianqi Liu, Huiqiang Sun +4
Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and i…
DreamMover: Leveraging the Prior of Diffusion Models for Image Interpolation with Large Motion
Liao Shen, Tianqi Liu, Huiqiang Sun +4
We study the problem of generating intermediate images from image pairs with large motion while maintaining semantic consistency. Due to the large motion, the intermediate semantic…
WildAvatar: Learning In-the-wild 3D Avatars from the Web
Zihao Huang, Shoukang Hu, Guangcong Wang +5
Existing research on avatar creation is typically limited to laboratory datasets, which require high costs against scalability and exhibit insufficient representation of the real w…
MVSGaussian: Fast Generalizable Gaussian Splatting Reconstruction from Multi-View Stereo
Tianqi Liu, Guangcong Wang, Shoukang Hu +6
We present MVSGaussian, a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) that can efficiently reconstruct unseen scenes. Specifically, 1…
Geometry-aware Reconstruction and Fusion-refined Rendering for Generalizable Neural Radiance Fields
Tianqi Liu, Xinyi Ye, Min Shi +4
Generalizable NeRF aims to synthesize novel views for unseen scenes. Common practices involve constructing variance-based cost volumes for geometry reconstruction and encoding 3D d…
3D Multi-frame Fusion for Video Stabilization
Zhan Peng, Xinyi Ye, Weiyue Zhao +4
In this paper, we present RStab, a novel framework for video stabilization that integrates 3D multi-frame fusion through volume rendering. Departing from conventional methods, we i…
When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo
Tianqi Liu, Xinyi Ye, Weiyue Zhao +3
Learning-based multi-view stereo (MVS) method heavily relies on feature matching, which requires distinctive and descriptive representations. An effective solution is to apply non-…