2 citations · 3 across the 6 of their papers we have counts for
6 papers
SiMDex: Mining Similar Egocentric Videos for Cross-Embodiment Dexterous Manipulation
Nie Lin, Takehiko Ohkawa, Sijin Chen +10
Recent years have witnessed an explosive trend of scaling ego-centric human videos for robot manipulation, yet it remains unclear which data actually benefits dexterous manipulatio…
Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention
Zhuohang Li, Liqun Huang, Wei Xu +5
Vision-Language-Action (VLA) models are prone to compounding errors in dexterous manipulation, where high-dimensional action spaces and contact-rich dynamics amplify small policy d…
SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training
Nie Lin, Takehiko Ohkawa, Yifei Huang +5
We present a framework for pre-training of 3D hand pose estimation from in-the-wild hand images sharing with similar hand characteristics, dubbed SimHand. Pre-training with large-s…
Pre-Training for 3D Hand Pose Estimation with Contrastive Learning on Large-Scale Hand Images in the Wild
Nie Lin, Takehiko Ohkawa, Mingfang Zhang +3
We present a contrastive learning framework based on in-the-wild hand images tailored for pre-training 3D hand pose estimators, dubbed HandCLR. Pre-training on large-scale images a…
Vision-Language Model Fine-Tuning via Simple Parameter-Efficient Modification
Ming Li, Jike Zhong, Chenxin Li +3
Recent advances in fine-tuning Vision-Language Models (VLMs) have witnessed the success of prompt tuning and adapter tuning, while the classic model fine-tuning on inherent paramet…
Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
Zicong Fan, Takehiko Ohkawa, Linlin Yang +21
We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic 3Dunderstanding of such interactions from egocentric views is important fo…