5 accepted papers
Loop closure detection in dynamic SLAM faces critical challenges when dynamic objects dominate camera views, degrading frame-to-frame methods reliant on static landmarks. We propose A-SPAM, an asynchronous framework that constructs spatiotemporal semantic graphs via semantic padding (entity tracking…
Loop closure detection in dynamic SLAM faces critical challenges when dynamic objects dominate camera views, degrading frame-to-frame methods reliant on static landmarks. We propose A-SPAM, an asynchronous framework that constructs spatiotemporal semantic graphs via semantic padding (entity tracking
Cross-modality pose estimation/localization is a critical challenge for multi-sensor-based perception systems, with applications spanning vehicle localization and online calibrations. In this paper, we introduce a hybrid approach to estimate the camera pose with respect to a point cloud with co-visi
Accurate identification of road intersections is the pivotal task for automatic construction of high-definition maps, particularly in unstructured scenes. Existing methods predominantly rely on single-modal data and thus show an obvious unimodal limitation, i.e., lack of contextual information. More…
Multi-modal image segmentation is one of the core issues in computer vision. The main challenge lies in integrating common information between modalities while retaining specific patterns for each modality. Existing methods typically perform full fine-tuning on RGB-based pre-trained parameters to in…