4 citations · 6 across the 8 of their papers we have counts for
8 papers
Y-BotFrame: An Extensible Embodied Agent Framework for Quadruped Robot Assistants
Luyao Zhang, Ke Li, Yuan Ding +9
Quadruped robots are capable of traversing a wide range of complex terrains with high flexibility. As highly mobile ground-based intelligent platforms, they can be equipped with mo…
AerialClaw: An Open-Source Framework for LLM-Driven Autonomous Aerial Agents
Ke Li, Jianfei Yang, Luyao Zhang +8
Unmanned aerial vehicles (UAVs) are increasingly used in inspection, search and rescue, environmental monitoring, and emergency response. However, most UAV applications still rely…
ProVG: Progressive Visual Grounding via Language Decoupling for Remote Sensing Imagery
Ke Li, Ting Wang, Di Wang +4
Remote sensing visual grounding (RSVG) aims to localize objects in remote sensing imagery according to natural language expressions. Previous methods typically rely on sentence-lev…
Improving Few-Shot Change Detection Visual Question Answering via Decision-Ambiguity-guided Reinforcement Fine-Tuning
Fuyu Dong, Ke Li, Di Wang +5
Change detection visual question answering (CDVQA) requires answering text queries by reasoning about semantic changes in bi-temporal remote sensing images. A straightforward appro…
Robust Drone-View Geo-Localization via Content-Viewpoint Disentanglement
Ke Li, Di Wang, Xiaowei Wang +4
Drone-view geo-localization (DVGL) aims to match images of the same geographic location captured from drone and satellite perspectives. Despite recent advances, DVGL remains challe…
FD2-Net: Frequency-Driven Feature Decomposition Network for Infrared-Visible Object Detection
Ke Li, Di Wang, Zhangyuan Hu +4
Infrared-visible object detection (IVOD) seeks to harness the complementary information in infrared and visible images, thereby enhancing the performance of detectors in complex en…
Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detection
Ke Li, Fuyu Dong, Di Wang +4
Remote sensing change detection aims to perceive changes occurring on the Earth's surface from remote sensing data in different periods, and feed these changes back to humans. Howe…
Robust Domain Generalization for Multi-modal Object Recognition
Yuxin Qiao, Keqin Li, Junhong Lin +4
In multi-label classification, machine learning encounters the challenge of domain generalization when handling tasks with distributions differing from the training data. Existing…