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Chaoyi Hong - IEEE Xplore Author Profile
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Chaoyi Hong

Publications
5
Citations
22
Publications by Year
20202025
Co-Authors:
Show All Co-Authors (19)
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Chaoyi Hong

Affiliation

School of AIA
Huazhong University of Science and Technology
Wuhan, China

Publication Topics

Biography

Chaoyi Hong is currently working toward the PhD degree with the School of Artificial Intelligence and Automation, Huazhong University of Science and Technology. Her research interests include dense prediction and aesthetics-related tasks, such as image matting and image cropping.(Based on document published on 8 October 2024).
Publications
5
Citations
22
Publications by Year
20202025
Co-Authors:
Show All Co-Authors (19)
Author's Published Works

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NVDS^{\mathbf{+}}+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation

Yiran Wang;Min Shi;Jiaqi Li;Chaoyi Hong;Zihao Huang;Juewen Peng;Zhiguo Cao;Jianming Zhang;Ke Xian;Guosheng Lin

IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2025 | Volume: 47, Issue: 1 | Journal Article |
Video depth estimation aims to infer temporally consistent depth. One approach is to finetune a single-image model on each video with geometry constraints, which proves inefficient and lacks robustness. An alternative is learning to enforce consistency from data, which requires well-designed models and sufficient video depth data. To address both challenges, we introduce NVDS$^{\mathbf{+}}$+ that ...Show More

NVDS$^{\mathbf{+}}$+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation

Yiran Wang;Min Shi;Jiaqi Li;Chaoyi Hong;Zihao Huang;Juewen Peng;Zhiguo Cao;Jianming Zhang;Ke Xian;Guosheng Lin

Year: 2025 | Volume: 47, Issue: 1 | Journal Article |

Unifying Automatic and Interactive Matting with Pretrained ViTs

Zixuan Ye;Wenze Liu;He Guo;Yujia Liang;Chaoyi Hong;Hao Lu;Zhiguo Cao

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Automatic and interactive matting largely improve image matting by respectively alleviating the need for auxil-iary input and enabling object selection. Due to different settings on whether prompts exist, they either suffer from weakness in instance completeness or region details. Also, when dealing with different scenarios, directly switching between the two matting models introduces inconvenienc...Show More

Unifying Automatic and Interactive Matting with Pretrained ViTs

Zixuan Ye;Wenze Liu;He Guo;Yujia Liang;Chaoyi Hong;Hao Lu;Zhiguo Cao

Year: 2024 | Conference Paper |

Composing Photos Like a Photographer

Chaoyi Hong;Shuaiyuan Du;Ke Xian;Hao Lu;Zhiguo Cao;Weicai Zhong

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2021 | Conference Paper |
Cited by: Papers (21)
We show that explicit modeling of composition rules benefits image cropping. Image cropping is considered a promising way to automate aesthetic composition in professional photography. Existing efforts, however, only model such professional knowledge implicitly, e.g., by ranking from comparative candidates. Inspired by the observation that natural composition traits always follow a specific rule, ...Show More

Composing Photos Like a Photographer

Chaoyi Hong;Shuaiyuan Du;Ke Xian;Hao Lu;Zhiguo Cao;Weicai Zhong

Year: 2021 | Conference Paper |

Parallel Network to Learn Novelty from the Known

Shuaiyuan Du;Chaoyi Hong;Zhiyu Pan;Chen Feng;Zhiguo Cao

2020 25th International Conference on Pattern Recognition (ICPR)
Year: 2021 | Conference Paper |
Towards multi-class novelty detection, we propose an end-to-end trainable Parallel Network (PN) using no additional data but only the training set. Our key idea is to first divide the training set into successive subtasks of pseudo-novelty detection to simulate real scenarios. We then design PN which consists of multiple branches to address the pseudo-tasks. This yields a more compact and discrmin...Show More

Parallel Network to Learn Novelty from the Known

Shuaiyuan Du;Chaoyi Hong;Zhiyu Pan;Chen Feng;Zhiguo Cao

Year: 2021 | Conference Paper |

Multi-Scale Attention Network for Image Cropping

Tianpei Lian;Ke Xian;Zhiyu Pan;Chaoyi Hong;Zhiguo Cao;Weicai Zhong

2020 Chinese Automation Congress (CAC)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Automatic image cropping is a completely practical but challenging task which aims to improve the aesthetic quality of an image by removing irrelevant areas. Most previous image cropping methods ignored compositional relationships among different regions of a given image. Global compositional relationships are extremely important for cropping models to decide whether to reserve a certain object of...Show More

Multi-Scale Attention Network for Image Cropping

Tianpei Lian;Ke Xian;Zhiyu Pan;Chaoyi Hong;Zhiguo Cao;Weicai Zhong

Year: 2020 | Conference Paper |

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