most citedCP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image Segmentation

3 citations · 5 across the 8 of their papers we have counts for

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cs.CV2026

CLIP-Guided Unsupervised Semantic-Aware Exposure Correction

Puzhen Wu, Han Weng, Quan Zheng +5

Improper exposure often leads to severe loss of details, color distortion, and reduced contrast. Exposure correction still faces two critical challenges: (1) the ignorance of objec…

cs.CV2025

Segregation and Context Aggregation Network for Real-time Cloud Segmentation

Yijie Li, Hewei Wang, Jiayi Zhang +5

Cloud segmentation from intensity images is a pivotal task in atmospheric science and computer vision, aiding weather forecasting and climate analysis. Ground-based sky/cloud segme…

cs.CV2025

Multi-Cali Anything: Dense Feature Multi-Frame Structure-from-Motion for Large-Scale Camera Array Calibration

Jinjiang You, Hewei Wang, Yijie Li +8

Calibrating large-scale camera arrays, such as those in dome-based setups, is time-intensive and typically requires dedicated captures of known patterns. While extrinsics in such a…

cs.CV2025★ 3 cited

CP2M: Clustered-Patch-Mixed Mosaic Augmentation for Aerial Image Segmentation

Yijie Li, Hewei Wang, Jinfeng Xu +4

Remote sensing image segmentation is pivotal for earth observation, underpinning applications such as environmental monitoring and urban planning. Due to the limited annotation dat…

cs.CV2025★ 2 cited

DDUNet: Dual Dynamic U-Net for Highly-Efficient Cloud Segmentation

Yijie Li, Hewei Wang, Jinfeng Xu +4

Cloud segmentation amounts to separating cloud pixels from non-cloud pixels in an image. Current deep learning methods for cloud segmentation suffer from three issues. (a) Constrai…