Search Results for author: Kunyang Lin

Found 5 papers, 3 papers with code

DCIR: Dynamic Consistency Intrinsic Reward for Multi-Agent Reinforcement Learning

no code implementations10 Dec 2023 Kunyang Lin, Yufeng Wang, Peihao Chen, Runhao Zeng, Siyuan Zhou, Mingkui Tan, Chuang Gan

In this paper, we propose a new approach that enables agents to learn whether their behaviors should be consistent with that of other agents by utilizing intrinsic rewards to learn the optimal policy for each agent.

Multi-agent Reinforcement Learning reinforcement-learning +2

Learning Vision-and-Language Navigation from YouTube Videos

1 code implementation ICCV 2023 Kunyang Lin, Peihao Chen, Diwei Huang, Thomas H. Li, Mingkui Tan, Chuang Gan

In this paper, we propose to learn an agent from these videos by creating a large-scale dataset which comprises reasonable path-instruction pairs from house tour videos and pre-training the agent on it.

Navigate Vision and Language Navigation

Instance Segmentation for Chinese Character Stroke Extraction, Datasets and Benchmarks

1 code implementation25 Oct 2022 Lizhao Liu, Kunyang Lin, Shangxin Huang, Zhongli Li, Chao Li, Yunbo Cao, Qingyu Zhou

Moreover, there are no standardized benchmarks to provide a fair comparison between different stroke extraction methods, which, we believe, is a major impediment to the development of Chinese character stroke understanding and related tasks.

Font Generation Instance Segmentation +2

Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation

1 code implementation14 Oct 2022 Peihao Chen, Dongyu Ji, Kunyang Lin, Runhao Zeng, Thomas H. Li, Mingkui Tan, Chuang Gan

To achieve accurate and efficient navigation, it is critical to build a map that accurately represents both spatial location and the semantic information of the environment objects.

Navigate Vision and Language Navigation

Learning Active Camera for Multi-Object Navigation

no code implementations14 Oct 2022 Peihao Chen, Dongyu Ji, Kunyang Lin, Weiwen Hu, Wenbing Huang, Thomas H. Li, Mingkui Tan, Chuang Gan

How to make robots perceive the environment as efficiently as humans is a fundamental problem in robotics.

Navigate Object

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