94 citations · 110 across the 15 of their papers we have counts for
15 papers
OmniContact: Chaining Meta-Skills via Contact Flow for Generalizable Humanoid Loco-Manipulation
Runyi Yu, Xiaoyi Lin, Ji Ma +11
Learning long-horizon humanoid loco-manipulation poses a dual challenge: it requires not only the robust execution of meta-skills but also their seamless, closed-loop chaining equi…
Switch: Learning Agile Skills Switching for Humanoid Robots
Yuen-Fui Lau, Qihan Zhao, Yinhuai Wang +4
Recent advancements in whole-body control through deep reinforcement learning have enabled humanoid robots to achieve remarkable progress in real-world chal lenging locomotion skil…
HumanX: Toward Agile and Generalizable Humanoid Interaction Skills from Human Videos
Yinhuai Wang, Qihan Zhao, Yuen Fui Lau +6
Enabling humanoid robots to perform agile and adaptive interactions has long been a core challenge in robotics. Current approaches are bottlenecked by either the scarcity of realis…
Learning Generalizable Hand-Object Tracking from Synthetic Demonstrations
Yinhuai Wang, Runyi Yu, Hok Wai Tsui +9
We present a system for learning generalizable hand-object tracking controllers purely from synthetic data, without requiring any human demonstrations. Our approach makes two key c…
SkillMimic-V2: Learning Robust and Generalizable Interaction Skills from Sparse and Noisy Demonstrations
Runyi Yu, Yinhuai Wang, Qihan Zhao +4
We address a fundamental challenge in Reinforcement Learning from Interaction Demonstration (RLID): demonstration noise and coverage limitations. While existing data collection app…
SkillMimic: Learning Basketball Interaction Skills from Demonstrations
Yinhuai Wang, Qihan Zhao, Runyi Yu +10
Traditional reinforcement learning methods for human-object interaction (HOI) rely on labor-intensive, manually designed skill rewards that do not generalize well across different…
PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interaction
Yinhuai Wang, Jing Lin, Ailing Zeng +3
Humans interact with objects all the time. Enabling a humanoid to learn human-object interaction (HOI) is a key step for future smart animation and intelligent robotics systems. Ho…
DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement
Shuzhou Yang, Xuanyu Zhang, Yinhuai Wang +3
Existing unsupervised low-light image enhancement methods lack enough effectiveness and generalization in practical applications. We suppose this is because of the absence of expli…
FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model
Jiwen Yu, Yinhuai Wang, Chen Zhao +2
Recently, conditional diffusion models have gained popularity in numerous applications due to their exceptional generation ability. However, many existing methods are training-requ…
Unlimited-Size Diffusion Restoration
Yinhuai Wang, Jiwen Yu, Runyi Yu +1
Recently, using diffusion models for zero-shot image restoration (IR) has become a new hot paradigm. This type of method only needs to use the pre-trained off-the-shelf diffusion m…
Position Embedding Needs an Independent Layer Normalization
Runyi Yu, Zhennan Wang, Yinhuai Wang +5
The Position Embedding (PE) is critical for Vision Transformers (VTs) due to the permutation-invariance of self-attention operation. By analyzing the input and output of each encod…
Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
Yinhuai Wang, Jiwen Yu, Jian Zhang
Most existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators. In this work, we propose the Denoising Diffusion Nul…
GAN Prior based Null-Space Learning for Consistent Super-Resolution
Yinhuai Wang, Yujie Hu, Jiwen Yu +1
Consistency and realness have always been the two critical issues of image super-resolution. While the realness has been dramatically improved with the use of GAN prior, the state-…
Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restoration
Yinhuai Wang, Yujie Hu, Jian Zhang
Emerging high-quality face restoration (FR) methods often utilize pre-trained GAN models (\textit{i.e.}, StyleGAN2) as GAN Prior. However, these methods usually struggle to balance…
NeRFocus: Neural Radiance Field for 3D Synthetic Defocus
Yinhuai Wang, Shuzhou Yang, Yujie Hu +1
Neural radiance fields (NeRF) bring a new wave for 3D interactive experiences. However, as an important part of the immersive experiences, the defocus effects have not been fully e…