1 citations · 1 across the 11 of their papers we have counts for
13 papers
HumanCLAW: Can Vision-Language Models Act Through a Body?
Li Siyao, Jiawei Gu, Shuai Liu +15
Evaluating whether a vision-language model (VLM) can act through a physical body is challenging. The outcome of an action couples the VLM's decision with motor control. When a task…
Ms. Forcing: Efficient Streaming Video Generation with Multi-Scale Patchification and Attention
Zekun Li, Xiaoyan Cong, Hongyu Li +5
Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoising loops of conventional n…
IAM: Identity-Aware Human Motion and Shape Joint Generation
Wenqi Jia, Zekun Li, Abhay Mittal +6
Recent advances in text-driven human motion generation enable models to synthesize realistic motion sequences from natural language descriptions. However, most existing approaches…
UMO: Unified In-Context Learning Unlocks Motion Foundation Model Priors
Xiaoyan Cong, Zekun Li, Zhiyang Dou +9
Large-scale foundation models (LFMs) have recently made impressive progress in text-to-motion generation by learning strong generative priors from massive 3D human motion datasets…
LLaMo: Scaling Pretrained Language Models for Unified Motion Understanding and Generation with Continuous Autoregressive Tokens
Zekun Li, Sizhe An, Chengcheng Tang +7
Recent progress in large models has led to significant advances in unified multimodal generation and understanding. However, the development of models that unify motion-language ge…
SMP: Reusable Score-Matching Motion Priors for Physics-Based Character Control
Yuxuan Mu, Ziyu Zhang, Yi Shi +9
Data-driven motion priors that can guide agents toward producing naturalistic behaviors play a pivotal role in creating life-like virtual characters. Adversarial imitation learning…
Pressure2Motion: Hierarchical Human Motion Reconstruction from Ground Pressure with Text Guidance
Zhengxuan Li, Qinhui Yang, Yiyu Zhuang +7
We present Pressure2Motion, a novel motion capture algorithm that reconstructs human motion from a ground pressure sequence and text prompt. At inference time, Pressure2Motion requ…
Sketch2PoseNet: Efficient and Generalized Sketch to 3D Human Pose Prediction
Li Wang, Yiyu Zhuang, Yanwen Wang +4
3D human pose estimation from sketches has broad applications in computer animation and film production. Unlike traditional human pose estimation, this task presents unique challen…
Efficient Learning of A Unified Policy For Whole-body Manipulation and Locomotion Skills
Dianyong Hou, Chengrui Zhu, Zhen Zhang +3
Equipping quadruped robots with manipulators provides unique loco-manipulation capabilities, enabling diverse practical applications. This integration creates a more complex system…
Sketch2Anim: Towards Transferring Sketch Storyboards into 3D Animation
Lei Zhong, Chuan Guo, Yiming Xie +2
Storyboarding is widely used for creating 3D animations. Animators use the 2D sketches in storyboards as references to craft the desired 3D animations through a trial-and-error pro…
Mixture of Scale Experts for Alignment-free RGBT Video Object Detection and A Unified Benchmark
Qishun Wang, Zhengzheng Tu, Kunpeng Wang +2
Existing RGB-Thermal Video Object Detection (RGBT VOD) methods predominantly rely on the manual alignment of image pairs, that is both labor-intensive and time-consuming. This depe…
MaskControl: Spatio-Temporal Control for Masked Motion Synthesis
Ekkasit Pinyoanuntapong, Muhammad Usama Saleem, Korrawe Karunratanakul +7
Recent advances in motion diffusion models have enabled spatially controllable text-to-motion generation. However, these models struggle to achieve high-precision control while mai…
MotionMix: Weakly-Supervised Diffusion for Controllable Motion Generation
Nhat M. Hoang, Kehong Gong, Chuan Guo +1
Controllable generation of 3D human motions becomes an important topic as the world embraces digital transformation. Existing works, though making promising progress with the adven…