computer-vision-2
Spatio-Temporal Video Grounding
3260 papers • 126 benchmarks • 313 datasets
Spatio-temporal video grounding is a computer vision and natural language processing (NLP) task that involves linking textual descriptions to specific spatio-temporal regions or moments in a video. In other words, it aims to determine which parts of a video correspond to a given textual query or description. This task is essential for various applications, including video summarization, content-based video retrieval, video captioning, and more.
(Image credit: Papersgraph)
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HC-STVG2
HC-STVG2
VidSTG
VidSTG
HC-STVG1
HC-STVG1
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Most implemented papers
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
Zhou Zhao, Zhu Zhang, Yang Zhao, Qi Wang, Huasheng Liu, Lianli Gao•Sat Jan 18 2020
A novel Spatio-Temporal Graph Reasoning Network (STGRN) is proposed for this task, which builds a spatio-temporal region graph to capture the region relationships with temporal object dynamics, which involves the implicit and explicit spatial subgraphs in each frame and the temporal dynamic subgraph across frames.
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