most citedMore Clear, More Flexible, More Precise: A Comprehensive Oriented Object Detection benchmark for UAV

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2026

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

Jianghang Lin, Haihua Yang, Deli Yu +6

Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional data curation strategies tha…

cs.CV2025

Evolving, Not Training: Zero-Shot Reasoning Segmentation via Evolutionary Prompting

Kai Ye, Xiaotong You, Jianghang Lin +3

Reasoning Segmentation requires models to interpret complex, context-dependent linguistic queries to achieve pixel-level localization. Current dominant approaches rely heavily on S…

eess.IV2025

Understanding What Is Not Said:Referring Remote Sensing Image Segmentation with Scarce Expressions

Kai Ye, Bowen Liu, Jianghang Lin +3

Referring Remote Sensing Image Segmentation (RRSIS) aims to segment instances in remote sensing images according to referring expressions. Unlike Referring Image Segmentation on ge…

cs.CV2025

RIS-LAD: A Benchmark and Model for Referring Low-Altitude Drone Image Segmentation

Kai Ye, YingShi Luan, Zhudi Chen +3

Referring Image Segmentation (RIS), which aims to segment specific objects based on natural language descriptions, plays an essential role in vision-language understanding. Despite…

cs.CV20251 cited

More Clear, More Flexible, More Precise: A Comprehensive Oriented Object Detection benchmark for UAV

Kai Ye, Haidi Tang, Bowen Liu +3

Applications of unmanned aerial vehicle (UAV) in logistics, agricultural automation, urban management, and emergency response are highly dependent on oriented object detection (OOD…

cs.CV2025

STeacher: Step-by-step Teacher for Sparsely Annotated Oriented Object Detection

Yu Lin, Jianghang Lin, Kai Ye +5

Although fully-supervised oriented object detection has made significant progress in multimodal remote sensing image understanding, it comes at the cost of labor-intensive annotati…