9 accepted papers
This paper presents a portable, cable-driven upper-limb rehabilitation robot designed for home-based activities of daily living (ADLs). The proposed robot is intended to assist hemiplegia patients with ADL-based rehabilitation, such as drinking water from a cup, in home settings. The robot features
Motion estimation in degraded scenes has long been a significant challenge, primarily attributed to substantial scene variations and insufficient training data. Existing approaches typically address this limitation by incorporating additional training strategies or modifying network architectures wi
Vision-Language Models (VLMs) like CLIP struggle to understand negation, often embedding affirmatives and negatives similarly (e.g., matching "no dog" with dog images). Existing methods refine negation understanding via fine-tuning CLIP’s text encoder, risking overfitting. In this work, we propose C
Although optical flow estimation has improved significantly in recent years, large displacements and occlusions remain challenging for current methods due to motion discontinuities that may hinder accurate feature correspondences in these regions, leading to degraded performance. To address this cha…
Vision-and-Language Navigation (VLN) tasks require an agent to follow textual instructions to navigate through 3D environments. Traditional approaches use supervised learning methods, relying heavily on domain-specific datasets to train VLN models. Recent methods try to utilize closedsource large la
The magnetic dipole model exhibits significant deviations from real-world sensor data due to neglected material nonlinearities and environmental interference. This paper proposed a Physics-Informed Residual Network (PIRNet) that adaptively corrected simulated magnetic field data by integrating dipol
Trajectory prediction in autonomous driving relies on accurate representation of all relevant contexts of the driving scene, including traffic participants, road topology, traffic signs, as well as their semantic relations to each other. Despite increased attention to this issue, most approaches in
In traditional Visual Question Generation (VQG), most images have multiple concepts (e.g. objects and categories) for which a question could be generated, but models are trained to mimic an arbitrary choice of concept as given in their training data. This makes training difficult and also poses issu…
The existing action tubelet detectors often depend on heuristic anchor design and placement, which might be computationally expensive and sub-optimal for precise localization. In this paper, we present a conceptually simple, computationally efficient, and more precise action tubelet detection framew…