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Shiwei Shen - IEEE Xplore Author Profile
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Shiwei Shen

Publications
4
Citations
1
Publications by Year
20152024
Co-Authors:
Show All Co-Authors (10)
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Shiwei Shen

Affiliation

School of Electrical and Control Engineering
Liaoning Technical University
Huludao, Liaoning Province, China

Publication Topics

Biography

Shiwei Shen received B.S. from Hangzhou Dianzi University (HDU) in electrical engineering in 2013 and now is an MSc student of HDU.(Based on document published on 14 January 2016).
Publications
4
Citations
1
Publications by Year
20152024
Co-Authors:
Show All Co-Authors (10)
Author's Published Works

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MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding

Bo He;Hengduo Li;Young Kyun Jang;Menglin Jia;Xuefei Cao;Ashish Shah;Abhinav Shrivastava;Ser-Nam Lim

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
With the success of large language models (LLMs), integrating the vision model into LLMs to build vision-language foundation models has gained much more interest recently. However, existing LLM-based large multimodal models (e.g., Video-LLaMA, VideoChat) can only take in a limited number of frames for short video understanding. In this study, we mainly focus on designing an efficient and effective...Show More

MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding

Bo He;Hengduo Li;Young Kyun Jang;Menglin Jia;Xuefei Cao;Ashish Shah;Abhinav Shrivastava;Ser-Nam Lim

Year: 2024 | Conference Paper |

Content-Aware Image Color Editing with Auxiliary Color Restoration Tasks

Yixuan Ren;Jing Shi;Zhifei Zhang;Yifei Fan;Zhe Lin;Bo He;Abhinav Shrivastava

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Year: 2024 | Conference Paper |
Diversified image color editing is typically modeled as a multimodal image-to-image translation (MMI2IT) problem with an impact on multiple applications such as photo enhancement and retouching. Although previous GAN-based algorithms successfully generate diverse edits with clear control, we observe two issues remaining: Firstly, they tend to apply the same color style to all kinds of input images...Show More

Content-Aware Image Color Editing with Auxiliary Color Restoration Tasks

Yixuan Ren;Jing Shi;Zhifei Zhang;Yifei Fan;Zhe Lin;Bo He;Abhinav Shrivastava

Year: 2024 | Conference Paper |

Align and Attend: Multimodal Summarization with Dual Contrastive Losses

Bo He;Jun Wang;Jielin Qiu;Trung Bui;Abhinav Shrivastava;Zhaowen Wang

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2023 | Conference Paper |
Cited by: Papers (26)
The goal of multimodal summarization is to extract the most important information from different modalities to form summaries. Unlike unimodal summarization, the multimodal summarization task explicitly leverages cross-modal information to help generate more reliable and high-quality summaries. However, existing methods fail to lever-age the temporal correspondence between different modal-ities an...Show More

Align and Attend: Multimodal Summarization with Dual Contrastive Losses

Bo He;Jun Wang;Jielin Qiu;Trung Bui;Abhinav Shrivastava;Zhaowen Wang

Year: 2023 | Conference Paper |

ASM-Loc: Action-aware Segment Modeling for Weakly-Supervised Temporal Action Localization

Bo He;Xitong Yang;Le Kang;Zhiyu Cheng;Xin Zhou;Abhinav Shrivastava

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2022 | Conference Paper |
Cited by: Papers (68)
Weakly-supervised temporal action localization aims to recognize and localize action segments in untrimmed videos given only video-level action labels for training. Without the boundary information of action segments, existing methods mostly rely on multiple instance learning (MIL), where the predictions of unlabeled instances (i.e., video snippets) are supervised by classifying labeled bags (i.e....Show More

ASM-Loc: Action-aware Segment Modeling for Weakly-Supervised Temporal Action Localization

Bo He;Xitong Yang;Le Kang;Zhiyu Cheng;Xin Zhou;Abhinav Shrivastava

Year: 2022 | Conference Paper |

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