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20162023
most citedFluency-Guided Cross-Lingual Image Captioning

97 citations · 333 across the 18 of their papers we have counts for

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Showing 2020 · cs.CVShow all

6 papers · 2 filters

cs.CV2020

Dual Encoding for Video Retrieval by Text

Jianfeng Dong, Xirong Li, Chaoxi Xu +4

This paper attacks the challenging problem of video retrieval by text. In such a retrieval paradigm, an end user searches for unlabeled videos by ad-hoc queries described exclusive…

cs.CV2020★ 11 cited

Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization

Daizong Liu, Xiaoye Qu, Xiao-Yang Liu +3

Query-based moment localization is a new task that localizes the best matched segment in an untrimmed video according to a given sentence query. In this localization task, one shou…

cs.CV2020★ 13 cited

Fine-grained Iterative Attention Network for TemporalLanguage Localization in Videos

Xiaoye Qu, Pengwei Tang, Zhikang Zhou +3

Temporal language localization in videos aims to ground one video segment in an untrimmed video based on a given sentence query. To tackle this task, designing an effective model t…

cs.CV2020★ 2 cited

Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval

Xun Yang, Jianfeng Dong, Yixin Cao +3

The rapid growth of user-generated videos on the Internet has intensified the need for text-based video retrieval systems. Traditional methods mainly favor the concept-based paradi…

cs.CV2020★ 17 cited

Feature Re-Learning with Data Augmentation for Video Relevance Prediction

Jianfeng Dong, Xun Wang, Leimin Zhang +3

Predicting the relevance between two given videos with respect to their visual content is a key component for content-based video recommendation and retrieval. Thanks to the increa…

cs.CV2020★ 1 cited

Fine-Grained Fashion Similarity Learning by Attribute-Specific Embedding Network

Zhe Ma, Jianfeng Dong, Yao Zhang +4

This paper strives to learn fine-grained fashion similarity. In this similarity paradigm, one should pay more attention to the similarity in terms of a specific design/attribute am…