366 citations · 396 across the 13 of their papers we have counts for
13 papers
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Yilin Wang, Chuan Guo, Yuxuan Mu +5
Generative masked transformers have demonstrated remarkable success across various content generation tasks, primarily due to their ability to effectively model large-scale dataset…
RegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation
Yilin Wang, Chuan Guo, Li Cheng +1
Can machine automatically generate multiple distinct and natural hand grasps, given specific contact region of an object in 3D? This motivates us to consider a novel task of \texti…
InterMask: 3D Human Interaction Generation via Collaborative Masked Modeling
Muhammad Gohar Javed, Chuan Guo, Li Cheng +1
Generating realistic 3D human-human interactions from textual descriptions remains a challenging task. Existing approaches, typically based on diffusion models, often produce resul…
GSD: View-Guided Gaussian Splatting Diffusion for 3D Reconstruction
Yuxuan Mu, Xinxin Zuo, Chuan Guo +7
We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D…
Generative Human Motion Stylization in Latent Space
Chuan Guo, Yuxuan Mu, Xinxin Zuo +4
Human motion stylization aims to revise the style of an input motion while keeping its content unaltered. Unlike existing works that operate directly in pose space, we leverage the…
MoMask: Generative Masked Modeling of 3D Human Motions
Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed +2
We introduce MoMask, a novel masked modeling framework for text-driven 3D human motion generation. In MoMask, a hierarchical quantization scheme is employed to represent human moti…
TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integration
Kehong Gong, Dongze Lian, Heng Chang +5
We propose a novel task for generating 3D dance movements that simultaneously incorporate both text and music modalities. Unlike existing works that generate dance movements using…
TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts
Chuan Guo, Xinxin Zuo, Sen Wang +1
Inspired by the strong ties between vision and language, the two intimate human sensing and communication modalities, our paper aims to explore the generation of 3D human full-body…
Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection
Wei Ji, Jingjing Li, Qi Bi +3
Growing interests in RGB-D salient object detection (RGB-D SOD) have been witnessed in recent years, owing partly to the popularity of depth sensors and the rapid progress of deep…
Action2video: Generating Videos of Human 3D Actions
Chuan Guo, Xinxin Zuo, Sen Wang +4
We aim to tackle the interesting yet challenging problem of generating videos of diverse and natural human motions from prescribed action categories. The key issue lies in the abil…
EventHPE: Event-based 3D Human Pose and Shape Estimation
Shihao Zou, Chuan Guo, Xinxin Zuo +6
Event camera is an emerging imaging sensor for capturing dynamics of moving objects as events, which motivates our work in estimating 3D human pose and shape from the event signals…
Human Pose and Shape Estimation from Single Polarization Images
Shihao Zou, Xinxin Zuo, Sen Wang +3
This paper focuses on a new problem of estimating human pose and shape from single polarization images. Polarization camera is known to be able to capture the polarization of refle…
Action2Motion: Conditioned Generation of 3D Human Motions
Chuan Guo, Xinxin Zuo, Sen Wang +5
Action recognition is a relatively established task, where givenan input sequence of human motion, the goal is to predict its ac-tion category. This paper, on the other hand, consi…