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From the 9 of 93 papers with an AI index.

most citedGWTC-4.0: Updating the Gravitational-Wave Transient Catalog with Observations from the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run

38 citations

Showing cs.CVShow all

8 papers · 1 filter

cs.CV202612 cited

The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

Kaiyuan Yang, Fabio Musio, Yihui Ma +112

The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…

cs.CV2026

StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset

Zhengqian Wu, Zhixian Liu, Aodong Chen +6

Video question answering (VideoQA) aims to answer questions about given videos. While existing approaches excel on factoid VideoQA, they struggle with deep video understanding (DVU…

cs.CV2026

APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds

Yuan Gao, Shaobo Xia, Sheng Nie +3

Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed in real-world scenarios often su…

cs.CV2026

MetaDent: Labeling Clinical Images for Vision-Language Models in Dentistry

Meng-Xun Li, Wen-Hui Deng, Zhi-Xing Wu +6

Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains largely underexplored due to…

cs.CV20262 cited

DeTracker: Motion-decoupled Vehicle Detection and Tracking in Unstabilized Satellite Videos

Jiajun Chen, Jing Xiao, Shaohan Cao +4

Satellite videos provide continuous observations of surface dynamics but pose significant challenges for multi-object tracking (MOT), especially under unstabilized conditions where…

cs.CV2026

Spatial-Spectral Adaptive Fidelity and Noise Prior Reduction Guided Hyperspectral Image Denoising

Xuelin Xie, Xiliang Lu, Zhengshan Wang +2

The core challenge of hyperspectral image denoising is striking the right balance between data fidelity and noise prior modeling. Most existing methods place too much emphasis on t…