Search Results for author: Hanqi Jiang

Found 5 papers, 2 papers with code

Eye-gaze Guided Multi-modal Alignment Framework for Radiology

1 code implementation19 Mar 2024 Chong Ma, Hanqi Jiang, WenTing Chen, Zihao Wu, Xiaowei Yu, Fang Zeng, Lei Guo, Dajiang Zhu, Tuo Zhang, Dinggang Shen, Tianming Liu, Xiang Li

Additionally, we explore the impact of varying amounts of eye-gaze data on model performance, highlighting the feasibility and utility of integrating this auxiliary data into multi-modal pre-training.

Zero-Shot Learning

LLMs for Coding and Robotics Education

no code implementations9 Feb 2024 Peng Shu, Huaqin Zhao, Hanqi Jiang, Yiwei Li, Shaochen Xu, Yi Pan, Zihao Wu, Zhengliang Liu, Guoyu Lu, Le Guan, Gong Chen, Xianqiao Wang Tianming Liu

To teach young children how to code and compete in robot challenges, large language models are being utilized for robot code explanation, generation, and modification.

Code Generation Explanation Generation

Large Language Models for Robotics: Opportunities, Challenges, and Perspectives

no code implementations9 Jan 2024 Jiaqi Wang, Zihao Wu, Yiwei Li, Hanqi Jiang, Peng Shu, Enze Shi, Huawen Hu, Chong Ma, Yiheng Liu, Xuhui Wang, Yincheng Yao, Xuan Liu, Huaqin Zhao, Zhengliang Liu, Haixing Dai, Lin Zhao, Bao Ge, Xiang Li, Tianming Liu, Shu Zhang

Notably, in the realm of robot task planning, LLMs harness their advanced reasoning and language comprehension capabilities to formulate precise and efficient action plans based on natural language instructions.

Robot Task Planning

Depth-NeuS: Neural Implicit Surfaces Learning for Multi-view Reconstruction Based on Depth Information Optimization

1 code implementation30 Mar 2023 Hanqi Jiang, Cheng Zeng, Runnan Chen, Shuai Liang, Yinhe Han, Yichao Gao, Conglin Wang

To address this problem, we propose a neural implicit surface learning method called Depth-NeuS based on depth information optimization for multi-view reconstruction.

Object Reconstruction Surface Reconstruction

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