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Published in CCC (oral), 2021
This paper develops the entire eel-like fish with a fully soft flexible body, which is composed of four fiber-reinforced, bidirectionally bending, fluidic elastomer actuators (FEAs) as its tail.
Recommended citation: Dang, Ronghao, et al. "Bionic Body Wave Control for an Eel-Like Robot Based on Segmented Soft Actuator Array." 2021 40th Chinese Control Conference (CCC). IEEE, 2021. http://academicpages.github.io/files/2021-7-26-Bionic Body Wave Control for an Eel-Like Robot Based on Segmented Soft Actuator Array.pdf
Published in AI COMMUNICATION, 2022
This paper applies the channel attention graph nerual network and multi-scale TCN significantly improves the skeleton-based action recognition
Recommended citation: Dang, Ronghao, et al. "Channel attention and multi-scale graph neural networks for skeleton-based action recognition." AI Communications Preprint (2022): 1-19 http://academicpages.github.io/files/CA-MSN.pdf
Published in ACMMM, 2022
This paper discovers the problem of object attention bias in visual object navigation tasks and solves it using directed object attention (DOA) graph.
Recommended citation: Dang, Ronghao, et al. "Unbiased Directed Object Attention Graph for Object Navigation." Proceedings of the 30th ACM International Conference on Multimedia. 2022. http://academicpages.github.io/files/Unbias_directed_object_attention_graph_for_object_navigation.pdf
Published in TCSVT, 2023
This work aims to improve the robustness and generalization of the navigator by dynamically providing high-quality pseudo-instructions using a proposed RES-StS paradigm.
Recommended citation: L. Wang, Z. He, R. Dang, H. Chen, C. Liu and Q. Chen, "RES-StS: Referring Expression Speaker via Self-training with Scorer for Goal-Oriented Vision-Language Navigation," in IEEE Transactions on Circuits and Systems for Video Technology. http://academicpages.github.io/files/RES-STS.pdf
Published in AI COMMUNICATION, 2023
This paper introduces a lightweight network, a Differential Learning and Parallel Convolutional Networks (DL-PCN), to reduce the computational burden of GCN skeleton action recognition method.
Recommended citation: Zeng, Qinyang, et al. "DL-PCN: Differential learning and parallel convolutional network for action recognition." AI Communications Preprint (2023): 1-15. https://content.iospress.com/articles/ai-communications/aic220268
Published in IJCAI, 2023
This work proposes a dual semantic-aware recurrent global-adaptive network (DSRG) to address two problems in VLN. (1) The explicit information mining for significant guiding semantics concealed in both vision and language is still under-explored; (2) The previously structured map method provides the average historical appearance of visited nodes, while it ignores distinctive contributions of various images and potent information retention in the reasoning process.
Recommended citation: Wang, Liuyi, et al. "A Dual Semantic-Aware Recurrent Global-Adaptive Network For Vision-and-Language Navigation." arXiv preprint arXiv:2305.03602 (2023). http://academicpages.github.io/files/DSRG.pdf
Published in ICML, 2023
This article proposes a new paradigm of meta-capability decoupling for Embodied AI tasks, which fully improves the interpretability, transferability and scalability of the model.
Recommended citation: Dang, Ronghao, et al. "Multiple thinking achieving meta-ability decoupling for object navigation." arXiv preprint arXiv:2302.01520 (2023). http://academicpages.github.io/files/MAD.pdf
Published in ICCV, 2023
This paper proposes a dual adaptive thinking (DAT) model, allowing the agent to adaptively adjust whether to use search thinking or navigation thinking in the process of object navigation.
Recommended citation: Dang, Ronghao, et al. "Search for or Navigate to? Dual Adaptive Thinking for Object Navigation." arXiv preprint arXiv:2208.00553 (2022). http://academicpages.github.io/files/Dual_Adaptive_Thinking_for_Object_Navigation.pdf
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Undergraduate course, Tongji University, Department, 2014
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Workshop, University 1, Department, 2015
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