56 citations · 111 across the 9 of their papers we have counts for
7 papers · 1 filter
Progressive Pseudo-Label Optimization for Point-Supervised Change Detection
Hailong Ning, Hao Wang, Yimeng Wang +3
Point-supervised change detection (PS-CD) aims to identify pixel-level changes between bi-temporal images using only sparsely annotated points. Although point annotations substanti…
ConInfer: Context-Aware Inference for Training-Free Open-Vocabulary Remote Sensing Segmentation
Wenyang Chen, Zhanxuan Hu, Yaping Zhang +2
Training-free open-vocabulary remote sensing segmentation (OVRSS), empowered by vision-language models, has emerged as a promising paradigm for achieving category-agnostic semantic…
Representation Discrepancy Bridging Method for Remote Sensing Image-Text Retrieval
Hailong Ning, Siying Wang, Tao Lei +5
Remote Sensing Image-Text Retrieval (RSITR) plays a critical role in geographic information interpretation, disaster monitoring, and urban planning by establishing semantic associa…
Lightweight Structure-aware Transformer Network for VHR Remote Sensing Image Change Detection
Tao Lei, Yetong Xu, Hailong Ning +4
Popular Transformer networks have been successfully applied to remote sensing (RS) image change detection (CD) identifications and achieve better results than most convolutional ne…
Delving into Rectifiers in Style-Based Image Translation
Yipeng Zhang, Bingliang Hu, Hailong Ning +1
While modern image translation techniques can create photorealistic synthetic images, they have limited style controllability, thus could suffer from translation errors. In this wo…
Audio-Visual Collaborative Representation Learning for Dynamic Saliency Prediction
Hailong Ning, Bin Zhao, Zhanxuan Hu +2
The Dynamic Saliency Prediction (DSP) task simulates the human selective attention mechanism to perceive the dynamic scene, which is significant and imperative in many vision tasks…
Bio-Inspired Representation Learning for Visual Attention Prediction
Yuan Yuan, Hailong Ning, Xiaoqiang Lu
Visual Attention Prediction (VAP) is a significant and imperative issue in the field of computer vision. Most of existing VAP methods are based on deep learning. However, they do n…