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20192023
most citedGeo-Localization via Ground-to-Satellite Cross-View Image Retrieval

52 citations · 86 across the 13 of their papers we have counts for

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7 papers · 1 filter

cs.CV20232 cited

A Generalized Physical-knowledge-guided Dynamic Model for Underwater Image Enhancement

Pan Mu, Hanning Xu, Zheyuan Liu +3

Underwater images often suffer from color distortion and low contrast resulting in various image types, due to the scattering and absorption of light by water. While it is difficul…

cs.CV2023

Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization

Jian Liang, Lijun Sheng, Zhengbo Wang +2

The emergence of vision-language models, such as CLIP, has spurred a significant research effort towards their application for downstream supervised learning tasks. Although some p…

cs.CV202311 cited

Improving Zero-Shot Generalization for CLIP with Synthesized Prompts

Zhengbo Wang, Jian Liang, Ran He +3

With the growing interest in pretrained vision-language models like CLIP, recent research has focused on adapting these models to downstream tasks. Despite achieving promising resu…

cs.CV2022

Context-Enhanced Stereo Transformer

Weiyu Guo, Zhaoshuo Li, Yongkui Yang +5

Stereo depth estimation is of great interest for computer vision research. However, existing methods struggles to generalize and predict reliably in hazardous regions, such as larg…

cs.CV202252 cited

Geo-Localization via Ground-to-Satellite Cross-View Image Retrieval

Zelong Zeng, Zheng Wang, Fan Yang +1

The large variation of viewpoint and irrelevant content around the target always hinder accurate image retrieval and its subsequent tasks. In this paper, we investigate an extremel…

cs.CV20224 cited

Lightweight Bimodal Network for Single-Image Super-Resolution via Symmetric CNN and Recursive Transformer

Guangwei Gao, Zhengxue Wang, Juncheng Li +3

Single-image super-resolution (SISR) has achieved significant breakthroughs with the development of deep learning. However, these methods are difficult to be applied in real-world…