11 accepted papers
We present a semantics modulated, multi scale Transformer for 3D gaze estimation. Our model conditions CLIP global features with learnable prototype banks (illumination, head pose, background, direction), fuses these prototype-enriched global vectors with CLIP patch tokens and high-resolution CNN to…
Ensuring safety in robotic manipulation is increasingly critical as robots become integrated into human-shared environments for complex physical interaction tasks. This paper presents an energy-aware control framework that combines active responses with passive compliance for safety-critical robotic
Ensuring safety in robotic manipulation is increasingly critical as robots become integrated into human-shared environments for complex physical interaction tasks. This paper presents an energy-aware control framework that combines active responses with passive compliance for safety-critical robotic…
As publicly available data dwindles, synthetic data generation (SDG) has become a practical solution for privacy-preserving data sharing. By training generative models on private data, SDG creates samples that retain task-relevant features while obfuscating sensitive content. However, recent work sh
With the rapid development of artificial intelligence (AI), especially in the medical field, the need for its explainability has grown. In medical image analysis, a high degree of transparency and model interpretability can help clinicians better understand and trust the decision-making process of A…
The potential of tactile sensing for dexterous robotic manipulation has been demonstrated by its ability to enable nuanced real-world interactions. In this study, the retrieval of unknown objects from confined spaces, which is unsuitable for conventional visual perception and gripper-based manipulat…
In recent years, Federated Learning (FL) has garnered significant attention as a distributed machine learning paradigm. To facilitate the implementation of the "right to be forgotten," the concept of federated machine unlearning (FMU) has also emerged. However, current FMU approaches often involve a…
"This paper studies semi-supervised video object segmentation through boosting intra-frame interaction. Recent memory network-based methods focus on exploiting inter-frame temporal reference while paying little attention to intra-frame spatial dependency. Specifically, these segmentation model tends…
"Recently, several spatial-temporal memory-based methods have verified that storing intermediate frames and their masks as memory are helpful to segment target objects in videos. However, they mainly focus on better matching between the current frame and the memory frames without explicitly paying a…
This paper presents a reactive legged locomotion generation scheme that enables our quadruped robot CEN-TAURO to adapt to varying payloads while walking. The center-of-mass (CoM) trajectories are generated in real time in a model predictive control (MPC) fashion, trading off large stability margins…
It is well-known that second-order optimizer can accelerate the training of deep neural networks, however, the huge computation cost of second-order optimization makes it impractical to apply in real practice. In order to reduce the cost, many methods have been proposed to approximate a second-order…