Log In Sign Up

A Simple Yet Effective Method for Video Temporal Grounding with Cross-Modality Attention

by   Binjie Zhang, et al.

The task of language-guided video temporal grounding is to localize the particular video clip corresponding to a query sentence in an untrimmed video. Though progress has been made continuously in this field, some issues still need to be resolved. First, most of the existing methods rely on the combination of multiple complicated modules to solve the task. Second, due to the semantic gaps between the two different modalities, aligning the information at different granularities (local and global) between the video and the language is significant, which is less addressed. Last, previous works do not consider the inevitable annotation bias due to the ambiguities of action boundaries. To address these limitations, we propose a simple two-branch Cross-Modality Attention (CMA) module with intuitive structure design, which alternatively modulates two modalities for better matching the information both locally and globally. In addition, we introduce a new task-specific regression loss function, which improves the temporal grounding accuracy by alleviating the impact of annotation bias. We conduct extensive experiments to validate our method, and the results show that just with this simple model, it can outperform the state of the arts on both Charades-STA and ActivityNet Captions datasets.


page 3

page 6

page 8


Unsupervised Temporal Video Grounding with Deep Semantic Clustering

Temporal video grounding (TVG) aims to localize a target segment in a vi...

Language-free Training for Zero-shot Video Grounding

Given an untrimmed video and a language query depicting a specific tempo...

Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding

Temporal grounding aims to localize temporal boundaries within untrimmed...

End-to-End Dense Video Grounding via Parallel Regression

Video grounding aims to localize the corresponding video moment in an un...

Dense Regression Network for Video Grounding

We address the problem of video grounding from natural language queries....

A Closer Look at Temporal Sentence Grounding in Videos: Datasets and Metrics

Despite Temporal Sentence Grounding in Videos (TSGV) has realized impres...

A Multi-level Alignment Training Scheme for Video-and-Language Grounding

To solve video-and-language grounding tasks, the key is for the network ...