9 accepted papers
Autonomous landing on mobile platforms is crucial for extending quadcopter operational flexibility, yet conventional methods are often too inefficient for highly dynamic scenarios. The core limitation lies in the prevalent “track-then-descend” paradigm, which treats the platform as a passive target
Explainability is essential for applying time series analysis in high-stakes domains. While Time Series Captioning (TSC) offers a pathway to enhance temporal explainability, achieving reliable caption generation usually necessitates high-quality textual annotations. However, as interpreting abstract…
Inferring 3D structures from sparse, unposed observations is challenging due to its unconstrained nature. Recent methods propose to predict implicit representations directly from unposed inputs in a data-driven manner, achieving promising results. However, these methods do not utilize geometric prio…
Change detection has consistently been a prominent direction in the field of remote sensing. As for high resolution remote sensing images (HRRSI), despite the notable achievements of change detection models, the majority of their impressive performance stems from their large scale architecture or co…
Mixed time series (MiTS) comprising both continuous variables (CVs) and discrete variables (DVs) are frequently encountered yet under-explored in time series analysis. Essentially, CVs and DVs exhibit different temporal patterns and distribution types. Overlooking these heterogeneities would lead to…
Simultaneous Localization and Mapping (SLAM) plays an important role in robot autonomy. Reliability and efficiency are the two most valued features for applying SLAM in robot applications. In this letter, we consider achieving a reliable LiDAR-based SLAM function in computation-limited platforms, su
Localizing an aggressively moving platform is a considerable challenge in the SLAM domain. This paper presents a dataset, SwiftBase, crafted to facilitate research into precise localization under such conditions. It includes high-speed cameras with over 200Hz sampling rate, capturing detailed visual…
Causal discovery under Granger causality framework has yielded widespread concerns in time series analysis task. Nevertheless, most previous methods are unaware of the underlying causality disappearing problem, that is, certain weak causalities are less focusable and may be lost during the modeling…
Accurate and timely onboard perception is a prerequisite for mobile robots to operate in highly dynamic scenarios. The bio-inspired event camera can capture more motion details than a traditional camera by triggering each pixel asynchronously and therefore is more suitable in such scenarios. Among v…