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20242026
most citedNWPU-MOC: A Benchmark for Fine-grained Multi-category Object Counting in Aerial Images

62 citations · 73 across the 23 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CV2026

Semantic-Aware Temporal Adaptation for UAV Anti-UAV Tracking

Xiaozhen Qiao, Da Zhang, Yubin Guo +3

UAV Anti-UAV tracking is an emerging low-altitude security task for localizing an adversarial UAV using the onboard camera of a moving observer UAV. It differs from conventional UA…

cs.LG2026

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

Da Zhang, Bingyu Li, Zhiyuan Zhao +3

Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existing methods struggle to jointl…

cs.CV2026

STAR-IOD: Scale-decoupled Topology Alignment with Pseudo-label Refinement for Remote Sensing Incremental Object Detection

Yaoteng Zhang, Qing Zhou, Junyu Gao +1

Remote sensing imagery typically arrives in the form of continuous data streams. Traditional detectors often forget previously learned categories when learning new ones; therefore,…

cs.CV2026

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting

Tao Han, Zhibin Wen, Zhenghao Chen +4

While AI-based numerical weather prediction (NWP) enables rapid forecasting, generating high-resolution outputs remains computationally demanding due to limited multi-scale adaptab…

cs.CV2026

Perturbation-Regularized Open-Vocabulary Remote Sensing Segmentation with Unified Multi-Domain Evaluation

Bingyu Li, Tao Huo, Haocheng Dong +4

Open-vocabulary remote sensing image segmentation (OVRSIS) aims to segment text-specified categories beyond a fixed label space. Its key challenge is to maintain reliable pixel--te…

cs.AI2026

Do MLLMs Really See It: Reinforcing Visual Attention in Multimodal LLMs

Siqu Ou, Tianrui Wan, Zhiyuan Zhao +2

While chain-of-thought (CoT) reasoning has substantially improved multimodal large language models (MLLMs) on complex reasoning tasks, existing approaches largely rely on long text…