arXiv:2604.22409v1 Announce Type: new
Abstract: Multimodal large language models (MLLMs) have advanced static visual–spatial reasoning, yet they often fail to preserve long-horizon spatial coherence in embodied settings where beliefs must be continuo…
arXiv:2604.22482v1 Announce Type: new
Abstract: While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3D datasets are predomin…
arXiv:2604.22506v1 Announce Type: new
Abstract: Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compression artifacts, and adverse imaging conditions ca…
arXiv:2604.19858v2 Announce Type: replace
Abstract: We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into professional-grade productivity tools. While con…
arXiv:2604.22212v1 Announce Type: cross
Abstract: In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-sectioning. Hence, it is natural to look at other mod…
arXiv:2604.22293v1 Announce Type: cross
Abstract: Lookup-table (LUT) based neural networks can deliver ultra-low latency and excellent hardware efficiency on FPGAs by mapping arithmetic operations directly onto the logic primitives. However, state-of-…
arXiv:2507.13706v2 Announce Type: replace
Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of the generalised optimal subpattern assignment (GOSPA)…
arXiv:2210.05513v2 Announce Type: replace
Abstract: We introduce ViFiCon, a self-supervised contrastive scheme which learns a cross-modal association between vision and wireless modalities. Specifically, the system uses pedestrian data collected from …
arXiv:2604.22177v1 Announce Type: new
Abstract: Multimodal MRI offers complementary information for brain tumor segmentation, but clinical scans often lack one or more modalities, which degrades segmentation performance. In this paper, we propose UniM…
arXiv:2604.22192v1 Announce Type: new
Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are fundamentally constrained by data-centric limitatio…