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cs.CV2023
ALL-E: Aesthetics-guided Low-light Image Enhancement
Ling Li, Dong Liang, Yuanhang Gao +2
Evaluating the performance of low-light image enhancement (LLE) is highly subjective, thus making integrating human preferences into image enhancement a necessity. Existing methods…
cs.CV2022★ 23 cited
MUS-CDB: Mixed Uncertainty Sampling with Class Distribution Balancing for Active Annotation in Aerial Object Detection
Dong Liang, Jing-Wei Zhang, Ying-Peng Tang +1
Recent aerial object detection models rely on a large amount of labeled training data, which requires unaffordable manual labeling costs in large aerial scenes with dense objects.…
cs.CV2022★ 16 cited
A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation
Feng Sun, Ming-Kun Xie, Sheng-Jun Huang
In this paper, we study the partial multi-label (PML) image classification problem, where each image is annotated with a candidate label set consists of multiple relevant labels an…