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20232026
most citedSemi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey

51 citations · 87 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024★ 16 cited

AdaSemiCD: An Adaptive Semi-Supervised Change Detection Method Based on Pseudo-Label Evaluation

Ran Lingyan, Wen Dongcheng, Zhuo Tao +3

Change Detection (CD) is an essential field in remote sensing, with a primary focus on identifying areas of change in bi-temporal image pairs captured at varying intervals of the s…

cs.CV2024★ 1 cited

Frequency-Guided Spatial Adaptation for Camouflaged Object Detection

Shizhou Zhang, Dexuan Kong, Yinghui Xing +5

Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that e…

cs.CV2024

Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation Approach

Shizhou Zhang, Wenlong Luo, De Cheng +4

In this paper, we construct a large-scale benchmark dataset for Ground-to-Aerial Video-based person Re-Identification, named G2A-VReID, which comprises 185,907 images and 5,576 tra…

cs.CV2024★ 16 cited

DDF: A Novel Dual-Domain Image Fusion Strategy for Remote Sensing Image Semantic Segmentation with Unsupervised Domain Adaptation

Lingyan Ran, Lushuang Wang, Tao Zhuo +1

Semantic segmentation of remote sensing images is a challenging and hot issue due to the large amount of unlabeled data. Unsupervised domain adaptation (UDA) has proven to be advan…

cs.CV2024★ 51 cited

Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey

Lingyan Ran, Yali Li, Guoqiang Liang +1

Semantic segmentation is an important and popular research area in computer vision that focuses on classifying pixels in an image based on their semantics. However, supervised deep…