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Junda Xu

3 accepted papers

2026

Revisiting the Necessity of Full Accuracy: Weakly Supervised Object-Level Offset Correction for Misaligned Building Labels

CVPR 2026

Google Earth imagery, combined with building footprint databases, offers an efficient way to construct localized building datasets. However, the lack of orthorectification in these images leads to spatial misalignments between annotations and their corresponding roof locations. Adopting such misalig

Cited by 0SourcecodeScholar
2025

Hazy Remote Sensing Image Semantic Segmentation with Weak Annotations via Pre-training Optimization and Co-training

ICASSP 2025accepted

In recent years, weakly supervised semantic segmentation has emerged as a prominent research topic in the field of remote sensing image semantic segmentation due to its cost-effective labeling advantages. However, the presence of haze in remote sensing images poses significant challenges to accurate…

Cited by 0SourceScholar
2024

Hazy Remote Sensing Images Semantic Segmentation for Weakly Annotation Based on Saliency-Aware Alignment Strategy

ICASSP 2024accepted

The technique of semantic segmentation (SS) holds significant importance in the domain of remote sensing image (RSI) processing. The current research primarily encompasses two problems: 1) RSIs are easily affected by clouds and haze; 2) SS based on strong annotation requires vast human and time cost…

Cited by 0SourceScholar