122 citations · 165 across the 8 of their papers we have counts for
8 papers
SentiAvatar: Towards Expressive and Interactive Digital Humans
Chuhao Jin, Rui Zhang, Qingzhe Gao +5
We present SentiAvatar, a framework for building expressive interactive 3D digital humans, and use it to create SuSu, a virtual character that speaks, gestures, and emotes in real…
ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking
Tingyang Zhang, Chen Wang, Zhiyang Dou +4
We propose ProTracker, a novel framework for accurate and robust long-term dense tracking of arbitrary points in videos. Previous methods relying on global cost volumes effectively…
Semantic Gesticulator: Semantics-Aware Co-Speech Gesture Synthesis
Zeyi Zhang, Tenglong Ao, Yuyao Zhang +4
In this work, we present Semantic Gesticulator, a novel framework designed to synthesize realistic gestures accompanying speech with strong semantic correspondence. Semantically me…
BAGS: Building Animatable Gaussian Splatting from a Monocular Video with Diffusion Priors
Tingyang Zhang, Qingzhe Gao, Weiyu Li +2
Animatable 3D reconstruction has significant applications across various fields, primarily relying on artists' handcraft creation. Recently, some studies have successfully construc…
Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images
Jiatao Gu, Qingzhe Gao, Shuangfei Zhai +3
Diffusion models have recently become the de-facto approach for generative modeling in the 2D domain. However, extending diffusion models to 3D is challenging due to the difficulti…
Rhythmic Gesticulator: Rhythm-Aware Co-Speech Gesture Synthesis with Hierarchical Neural Embeddings
Tenglong Ao, Qingzhe Gao, Yuke Lou +2
Automatic synthesis of realistic co-speech gestures is an increasingly important yet challenging task in artificial embodied agent creation. Previous systems mainly focus on genera…
Neural Novel Actor: Learning a Generalized Animatable Neural Representation for Human Actors
Yiming Wang, Qingzhe Gao, Libin Liu +3
We propose a new method for learning a generalized animatable neural human representation from a sparse set of multi-view imagery of multiple persons. The learned representation ca…
Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu +1
Co-part segmentation is an important problem in computer vision for its rich applications. We propose an unsupervised learning approach for co-part segmentation from images. For th…