1 citations · 1 across the 7 of their papers we have counts for
7 papers
Collaborative Temporal Consistency Learning for Point-supervised Natural Language Video Localization
Zhuo Tao, Liang Li, Qi Chen +5
Natural language video localization (NLVL) is a crucial task in video understanding that aims to localize the target moment in videos specified by a given language description. Rec…
Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning
Yunbin Tu, Liang Li, Li Su +1
Video has emerged as a favored multimedia format on the internet. To better gain video contents, a new topic HIREST is presented, including video retrieval, moment retrieval, momen…
Distractors-Immune Representation Learning with Cross-modal Contrastive Regularization for Change Captioning
Yunbin Tu, Liang Li, Li Su +2
Change captioning aims to succinctly describe the semantic change between a pair of similar images, while being immune to distractors (illumination and viewpoint changes). Under th…
Context-aware Difference Distilling for Multi-change Captioning
Yunbin Tu, Liang Li, Li Su +3
Multi-change captioning aims to describe complex and coupled changes within an image pair in natural language. Compared with single-change captioning, this task requires the model…
Self-supervised Cross-view Representation Reconstruction for Change Captioning
Yunbin Tu, Liang Li, Li Su +3
Change captioning aims to describe the difference between a pair of similar images. Its key challenge is how to learn a stable difference representation under pseudo changes caused…
Neighborhood Contrastive Transformer for Change Captioning
Yunbin Tu, Liang Li, Li Su +2
Change captioning is to describe the semantic change between a pair of similar images in natural language. It is more challenging than general image captioning, because it requires…
RNet:Relation-embedded Representation Reconstruction Network for Change Captioning
Yunbin Tu, Liang Li, Chenggang Yan +2
Change captioning is to use a natural language sentence to describe the fine-grained disagreement between two similar images. Viewpoint change is the most typical distractor in thi…