110 citations · 172 across the 9 of their papers we have counts for
10 papers
MIND: Multi-Scale Intent Diffusion for Text-Driven Physics-Based Humanoid Control
Bin Li, Ruichi Zhang, Han Liang +4
Enabling physics-based humanoids to execute diverse behaviors from high-level textual commands remains a significant challenge. Existing methods typically follow either a two-stage…
InterAgent: Physics-based Multi-agent Command Execution via Diffusion on Interaction Graphs
Bin Li, Ruichi Zhang, Han Liang +6
Humanoid agents are expected to emulate the complex coordination inherent in human social behaviors. However, existing methods are largely confined to single-agent scenarios, overl…
LLaVA-SLT: Visual Language Tuning for Sign Language Translation
Han Liang, Chengyu Huang, Yuecheng Xu +6
In the realm of Sign Language Translation (SLT), reliance on costly gloss-annotated datasets has posed a significant barrier. Recent advancements in gloss-free SLT methods have sho…
Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance
Qingcheng Zhao, Pengyu Long, Qixuan Zhang +6
The synthesis of 3D facial animations from speech has garnered considerable attention. Due to the scarcity of high-quality 4D facial data and well-annotated abundant multi-modality…
OMG: Towards Open-vocabulary Motion Generation via Mixture of Controllers
Han Liang, Jiacheng Bao, Ruichi Zhang +6
We have recently seen tremendous progress in realistic text-to-motion generation. Yet, the existing methods often fail or produce implausible motions with unseen text inputs, which…
InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions
Han Liang, Wenqian Zhang, Wenxuan Li +2
We have recently seen tremendous progress in diffusion advances for generating realistic human motions. Yet, they largely disregard the multi-human interactions. In this paper, we…
LiDAR-aid Inertial Poser: Large-scale Human Motion Capture by Sparse Inertial and LiDAR Sensors
Yiming Ren, Chengfeng Zhao, Yannan He +5
We propose a multi-sensor fusion method for capturing challenging 3D human motions with accurate consecutive local poses and global trajectories in large-scale scenarios, only usin…
HybridCap: Inertia-aid Monocular Capture of Challenging Human Motions
Han Liang, Yannan He, Chengfeng Zhao +4
Monocular 3D motion capture (mocap) is beneficial to many applications. The use of a single camera, however, often fails to handle occlusions of different body parts and hence it i…
ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References
Yannan He, Anqi Pang, Xin Chen +4
Capturing challenging human motions is critical for numerous applications, but it suffers from complex motion patterns and severe self-occlusion under the monocular setting. In thi…
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration
Zhong Zhao, Yanmei Fu, Hanming Liang +3
In feeds recommendation, the first step is candidate generation. Most of the candidate generation models are based on CTR estimation, which do not consider user's satisfaction with…