Chenyu GAO
(高晨雨)

							@inproceedings{gao2023pendular,
								title={The pendular graph: Visualising hierarchical repetitive structure in point-set representations of the POP909 music dataset},
								author={Gao, Chenyu and Collins, Tom},
								booktitle={Proceedings of the Human-Computer Interaction International Conference},
								year={2023}
							  }

							@article{gao2021structured,
								title={Structured multimodal attentions for textvqa},
								author={Gao, Chenyu and Zhu, Qi and Wang, Peng and Li, Hui and Liu, Yuliang and Van den Hengel, Anton and Wu, Qi},
								journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
								volume={44},
								number={12},
								pages={9603--9614},
								year={2021},
								publisher={IEEE}
							  }

							@article{gao2021chop,
								title={Chop Chop BERT: Visual Question Answering by Chopping VisualBERT’s Heads},
								author={Gao, Chenyu and Zhu, Qi and Wang, Peng and Wu, Qi},
								booktitle={30th International Joint Conference on Artificial Intelligence},
								year={2021}
							  }

							@inproceedings{zhu2020ssbaseline,
								title={Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps},
								author={Zhu, Qi and Gao, Chenyu and Wang, Peng and Wu, Qi},
								booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
								year={2021}
							  }
						

							@inproceedings{gao2019mobilecount,
								title={MobileCount: An Efficient Encoder-Decoder Framework for Real-Time Crowd Counting},
								author={Gao, Chenyu and Wang, Peng and Gao, Ye},
								booktitle={Chinese Conference on Pattern Recognition and Computer Vision (PRCV)},
								pages={582--595},
								year={2019},
								organization={Springer}
							  }
							  @article{wang2020mobilecount,
								title={MobileCount: An Efficient Encoder-Decoder Framework for Real-Time Crowd Counting},
								author={Wang, Peng and Gao, Chenyu and Wang, Yang and Li, Hui and Gao, Ye},
								journal={Neurocomputing},
								year={2020},
								publisher={Elsevier}
							  }

							@article{gao2019c,
								title={C$^3$ Framework: An Open-source PyTorch Code for Crowd Counting},
								author={Gao, Junyu and Lin, Wei and Zhao, Bin and Wang, Dong and Gao, Chenyu and Wen, Jun},
								journal={arXiv preprint arXiv:1907.02724},
								year={2019}
								}