2 citations · 4 across the 16 of their papers we have counts for
11 papers · 1 filter
Where am I? Cross-View Geo-localization with Natural Language Descriptions
Junyan Ye, Honglin Lin, Leyan Ou +5
Cross-view geo-localization identifies the locations of street-view images by matching them with geo-tagged satellite images or OSM. However, most existing studies focus on image-t…
LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models
Junyan Ye, Baichuan Zhou, Zilong Huang +12
With the rapid development of AI-generated content, the future internet may be inundated with synthetic data, making the discrimination of authentic and credible multimodal data in…
Fine-Grained Building Function Recognition from Street-View Images via Geometry-Aware Semi-Supervised Learning
Weijia Li, Jinhua Yu, Dairong Chen +5
In this work, we propose a geometry-aware semi-supervised framework for fine-grained building function recognition, utilizing geometric relationships among multi-source data to enh…
CrossViewDiff: A Cross-View Diffusion Model for Satellite-to-Street View Synthesis
Weijia Li, Jun He, Junyan Ye +5
Satellite-to-street view synthesis aims at generating a realistic street-view image from its corresponding satellite-view image. Although stable diffusion models have exhibit remar…
Cross-view image geo-localization with Panorama-BEV Co-Retrieval Network
Junyan Ye, Zhutao Lv, Weijia Li +4
Cross-view geolocalization identifies the geographic location of street view images by matching them with a georeferenced satellite database. Significant challenges arise due to th…
UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarios
Baichuan Zhou, Haote Yang, Dairong Chen +7
Recent evaluations of Large Multimodal Models (LMMs) have explored their capabilities in various domains, with only few benchmarks specifically focusing on urban environments. More…
Leveraging BEV Paradigm for Ground-to-Aerial Image Synthesis
Junyan Ye, Jun He, Weijia Li +5
Ground-to-aerial image synthesis focuses on generating realistic aerial images from corresponding ground street view images while maintaining consistent content layout, simulating…
SynthVLM: Towards High-Quality and Efficient Synthesis of Image-Caption Datasets for Vision-Language Models
Zheng Liu, Hao Liang, Bozhou Li +5
Vision-Language Models (VLMs) have recently emerged, demonstrating remarkable vision-understanding capabilities. However, training these models requires large-scale datasets, which…
3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level Supervisions
Weijia Li, Haote Yang, Zhenghao Hu +3
3D building reconstruction from monocular remote sensing images is an important and challenging research problem that has received increasing attention in recent years, owing to it…
SG-BEV: Satellite-Guided BEV Fusion for Cross-View Semantic Segmentation
Junyan Ye, Qiyan Luo, Jinhua Yu +4
This paper aims at achieving fine-grained building attribute segmentation in a cross-view scenario, i.e., using satellite and street-view image pairs. The main challenge lies in ov…
Parrot Captions Teach CLIP to Spot Text
Yiqi Lin, Conghui He, Alex Jinpeng Wang +3
Despite CLIP being the foundation model in numerous vision-language applications, the CLIP suffers from a severe text spotting bias. Such bias causes CLIP models to `Parrot' the vi…