9 accepted papers
Building reconstruction aims to extract compact wireframes from point clouds. Recent edge-based methods achieve impressive results but suffer from sparse supervision from one-to-one matching, which leaves most edge proposals under-optimized. In this paper, we present Group Relative Edge Optimization
Autonomous object detection in remote sensing requires systems that can discover new categories and assign them usable labels during deployment. Existing Open-World Object Detectors identify unknown objects but leave them unnamed until manual annotation. In contrast, Open-Vocabulary Detectors recogn
Land-air bimodal robots (LABR) are gaining attention for autonomous navigation, combining high mobility from aerial vehicles with long endurance from ground vehicles. However, existing LABR navigation methods are limited by suboptimal trajectories from mapping-based approaches and the excessive comp
This paper presents a lightweight bidirectional cable-driven ankle exoskeleton system (total mass: 2.6 kg) based on a series elastic actuation architecture (actuator module mass: 1.05 kg). The system utilizes a waist-mounted drive unit and Bowden cables to deliver bidirectional assistance to the ank
Most publicly accessible remote sensing data suffer from low resolution, limiting their practical applications. To address this, we propose a diffusion model guided by neural operators (NO) for continuous remote sensing image super-resolution (NeurOp-Diff). Neural operators are used to learn resolut…
Multi-agent cooperative SLAM often encounters challenges in similar indoor environments characterized by repetitive structures, such as corridors and rooms. These challenges can lead to significant inaccuracies in shared location identification when employing point cloud-based techniques. To mitigat
With the rapid development of LLMs, the evaluation of factual consistency between source documents and generated texts plays a more crucial role in natural language generation (NLG). Recent methods usually suffer from low quality and insufficient quantity of training data. In this paper, we propose…
Shadows often incur uneven illumination to pavement images, which brings great challenges to image-based pavement crack detection. Thus, it is desired to remove pavement shadows before detecting pavement cracks. However, due to the large penumbras cast by trees, light poles, etc., it is difficult to…