5 accepted papers
3D Gaussian splatting (3DGS) has emerged as a revolutionary scene representation in simultaneous localization and mapping (SLAM) research. However, existing research on 3DGS-based SLAM fails to accurately address the appearance variations induced by camera auto-exposure in prevalent real-world scena
Theory of Mind (ToM) refers to the ability to infer others' mental states, such as beliefs, desires, and intentions. Current vision-language embodied agents lack ToM-based decision-making, and existing benchmarks focus solely on human mental states while ignoring the agent's own perspective, hinderi
Point cloud semantic segmentation is crucial in various applications such as autonomous driving, robotics, and virtual reality, aiming to assign labels to each point in a cloud to reflect spatial relationships and boundaries. While previous methods primarily focus on geometric features, they often o
Loop Closure Detection (LCD) is an essential component of Simultaneous Localization and Mapping (SLAM), helping to correct drift errors, facilitate map merging, or both by identifying previously observed scenes. Despite its importance, traditional LCD algorithms based on single sensor such as camera…
In indoor scenes, pose estimation drift in SLAM systems is challenging to mitigate due to factors like low texture and texture repetition. Several studies utilize Manhattan structural information to achieve low-drift rotation estimation consequently reducing the cumulative error. However, the applic