24 accepted papers
Lower extremity exoskeletons designed for multi-joint assistance are increasingly explored for rehabilitation and human augmentation. However, conventional monoarticular designs often suffer from joint misalignment and actuator redundancy, limiting their efficiency and user comfort. This study prese…
The Segment Anything Model 2 (SAM2) has emerged as a foundation model for universal segmentation. Owing to its generalizable visual representations, SAM2 has been successfully applied to various downstream tasks. However, extending SAM2 to the RGB-D video salient object detection (RGB-D VSOD) task e
Recently segment anything model (SAM) has attracted widespread concerns, and it is often treated as a vision foundation model for universal segmentation. Some researchers have attempted to directly apply the foundation model to the RGB-D video salient object detection (RGB-D VSOD) task, which often
Ultrasound standard plane recognition is essential for clinical tasks such as disease screening, organ evaluation, and biometric measurement. However, existing methods fail to effectively exploit shallow structural information and struggle to capture fine-grained semantic differences through contras
Spiking Neural Networks (SNNs) offer a promising, energy-efficient paradigm for computation, but their practical application is hindered by challenges in architecture design and training costs. For example, Spiking ResNet exhibits relatively low performance, whereas high-performance Spiking Transfor…
Guided depth super-resolution (GDSR) has demonstrated impressive performance across a wide range of domains, with numerous methods being proposed. However, existing methods often treat depth maps as images, where shading values are computed discretely, making them struggle to effectively restore the…
Knowledge summarization task aims to summarize the knowledge scattered in multiple documents for answering a query. In this paper, we adopt the concept relation knowledge base ConceptNet for the task and propose the ConceptNet integrated summarization method CNSum, where the concepts are adopted as…
Socratic teaching, known for its emphasis on heuristic questioning and deep thinking, has demonstrated significant advantages in promoting students’ cognitive development. However, traditional Socratic teaching places high demands on teachers’ expertise and real-time feedback capabilities, making it
Stance detection aims to identify the attitude expressed in text towards a specific target. Recent studies on zero-shot and few-shot stance detection focus primarily on learning generalized representations from explicit targets. However, these methods often neglect implicit yet semantically importan
Reconstructing 3D shapes from a single image plays an important role in computer vision. Many methods have been proposed and achieve impressive performance. However, existing methods mainly focus on extracting semantic information from images and then simply concatenating it with 3D point clouds wit…
Although semi-supervised learning has made significant advances in the field of medical image segmentation, fully annotating a volumetric sample slice by slice remains a costly and time-consuming task. Even worse, most of the existing approaches pay much attention to image-level information and igno…
To minimize discomfort and injury risk in exoskeleton users, this paper addresses the misalignment between the device and the human knee joint. The knee's spatial motion complexity, characterized by multi-planar rotation axes as flexion angle changes, cannot be accurately replicated by existing sing
Public libraries are an essential public good. We ask: are urban library systems providing equitable service to all residents, in terms of the books they have access to and check out? If not, what causes disparities: heterogeneous book collections, resident behavior and access, and/or operational po…
In the labor-intensive Roll-On/Roll-Off (RO/RO) terminal environment, research on vehicle transport robots with mobility, stability, and reliability is receiving increasing attention. This paper presents a novel control framework for a Straddle-Type Dual-Body vehicle transfer robot. Initially, fine…
Since Rendle and Krichene argued that commonly used sampling-based evaluation metrics are ``inconsistent'' with respect to the global metrics (even in expectation), there have been a few studies on the sampling-based recommender system evaluation. Existing methods try either mapping the sampling-bas…
In this work, we propose PolarBEV for vision-based uneven BEV representation learning. To adapt to the foreshortening effect of camera imaging, we rasterize the BEV space both angularly and radially, and introduce polar embedding decomposition to model the associations among polar grids. Polar gri…
Soft climbing robots have been attracting increasing attention in soft robotics community, and a lot of prototypes been proposed with basic climbing function implemented. Climbing on poles is a challenge with soft robots, and the capability of current pole-climbing soft robots needs to be improved i…
Since the recent studies (KDD'20) done by Krichene and Rendle on the sampling based top-k evaluation metric for recommendation, there have been a lot of debate on the validity of using sampling for evaluating recommendation algorithms. Though their work and the recent work done by Li et. al. (KDD'…
Existing learned-based image compression methods have shown impressive performance. However, most of them rely on the consistency of distribution between training images and test images, which limits the robustness of the trained model. In this paper, we propose a novel compression method called spa…
Depth maps contain geometric clues for assisting Salient Object Detection (SOD). In this paper, we propose a novel Cross-Modal Weighting (CMW) strategy to encourage comprehensive interactions between RGB and depth channels for RGB-D SOD. Specifically, three RGB-depth interaction modules, named CMW-L…
Deep neural networks (DNNs) have recently achieved impressive performances on various applications. However, recent researches show that DNNs are vulnerable to adversarial perturbations injected into input samples. In this paper, we investigate a defense method for face verification: a deep residual…
We consider the problem of referring image segmentation. Given an input image and a natural language expression, the goal is to segment the object referred by the language expression in the image. Existing works in this area treat the language expression and the input image separately in their repre…
Solving the global method of Weighted Least Squares (WLS) model in image filtering is both time- and memory-consuming. In this paper, we present an alternative approximation in a time- and memory- efficient manner which is denoted as Semi-Global Weighed Least Squares (SG-WLS). Instead of solving a l…
In this paper, we propose a multi-stage depth-aware saliency model for salient region detection. We evaluate saliency on different features at low, mid and high levels, by taking account of primary depth and appearance contrasts, different feature weighted factors and location priors, respectively.…