2 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
EfficientSync: Real-Time Lip Synchronization via Deformation-Based Reference Texture Mixing
Fa-Ting Hong, Runzhen Liu, Luchuan Song +2
Audio-driven lip synchronization manipulates the mouth region of a talking-face video to match the driving audio while preserving head pose, identity, and background. Although the…
SplitAvatar: One-shot Head Avatar with Autoregressive Gaussian Splitting
Hongzhe Liao, Chuhua Xian, Hongmin Cai +2
3D Gaussian Splatting (3DGS) provides an efficient method for high-quality scene reconstruction using anisotropic Gaussians. Recently, 3DGS-based methods have significantly improve…
AtomicMotion: Learning Human Motion From Different Human Parts
Runzhen Liu, Chuhua Xian, Fa-Ting Hong
Accurately reconstructing full-body poses from sparse head and hand trajectories is a foundational challenge for immersive AR/VR telepresence. Current methods often struggle with e…
Identity-Preserving Video Dubbing Using Motion Warping
Runzhen Liu, Qinjie Lin, Yunfei Liu +5
Video dubbing aims to synthesize realistic, lip-synced videos from a reference video and a driving audio signal. Although existing methods can accurately generate mouth shapes driv…
Consistent Depth Prediction under Various Illuminations using Dilated Cross Attention
Zitian Zhang, Chuhua Xian
In this paper, we aim to solve the problem of consistent depth prediction in complex scenes under various illumination conditions. The existing indoor datasets based on RGB-D senso…
Multi-Scale Progressive Fusion Learning for Depth Map Super-Resolution
Chuhua Xian, Kun Qian, Zitian Zhang +1
Limited by the cost and technology, the resolution of depth map collected by depth camera is often lower than that of its associated RGB camera. Although there have been many resea…
Fast Generation of High Fidelity RGB-D Images by Deep-Learning with Adaptive Convolution
Chuhua Xian, Dongjiu Zhang, Chengkai Dai +1
Using the raw data from consumer-level RGB-D cameras as input, we propose a deep-learning based approach to efficiently generate RGB-D images with completed information in high res…