← Search

Jinhua Yu

7 accepted papers

2026

Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents

ICLR 2026poster

Earth observation (EO) is essential for understanding the evolving states of the Earth system. Although recent MLLMs have advanced EO research, they still lack the capability to tackle complex tasks that require multi-step reasoning and the use of domain-specific tools. Agent-based methods offer a…

Cited by 0SourcecodeScholar
2026

GMENet: Generative Mixture of Experts Network for Multi-Center Glioma Diagnosis with Incomplete Imaging Sequences

IJCAI 2026

Contemporary glioma diagnosis integrates molecular features with histopathology to guide clinical decision-making. However, in clinical settings, divergent imaging protocols result in incomplete MRI sequences, leading to two primary challenges: forcing existing frameworks to discard a large portion

Cited by 0Scholar
2025

Leveraging BEV Paradigm for Ground-to-Aerial Image Synthesis

ICCV 2025poster

Ground-to-aerial image synthesis focuses on generating realistic aerial images from corresponding ground street view images while maintaining consistent content layout, simulating a top-down view. The significant viewpoint difference leads to domain gaps between views, and dense urban scenes limit t…

2025

UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarios

AAAI 2025technical

Recent evaluations of Large Multimodal Models (LMMs) have explored their capabilities in various domains, with only few benchmarks specifically focusing on urban environments. Moreover, existing urban benchmarks have been limited to evaluating LMMs with basic region-level urban tasks under singular…

2024

Cross-view image geo-localization with Panorama-BEV Co-Retrieval Network

ECCV 2024poster

"Cross-view geolocalization identifies the geographic location of street view images by matching them with a georeferenced satellite database. Significant challenges arise due to the drastic appearance and geometry differences between views. In this paper, we propose a new approach for cross-view im…

2024

SG-BEV: Satellite-Guided BEV Fusion for Cross-View Semantic Segmentation

CVPR 2024highlight

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 overcoming the significant perspective differences between street views and satellite views. In this work we introduce SG-BE…

2023

OmniCity: Omnipotent City Understanding With Multi-Level and Multi-View Images

CVPR 2023poster

This paper presents OmniCity, a new dataset for omnipotent city understanding from multi-level and multi-view images. More precisely, OmniCity contains multi-view satellite images as well as street-level panorama and mono-view images, constituting over 100K pixel-wise annotated images that are well-…