Related papers: An empirical study of the effect of video encoders on Temporal Video Grounding

An empirical study of the effect of video encoders on Temporal Video Grounding

URL: http://arxiv.org/abs/2510.17007v1
Date: Sun, 19 Oct 2025 21:10:43 GMT
Title: An empirical study of the effect of video encoders on Temporal Video Grounding
Authors: Ignacio M. De la Jara, Cristian Rodriguez-Opazo, Edison Marrese-Taylor, Felipe Bravo-Marquez,
Abstract summary: We propose an empirical study to investigate the impact of different video features on a classical architecture.<n>Our results show significant differences in the performance of our model by simply changing the video encoder.
Score: 12.414978847277853
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Temporal video grounding is a fundamental task in computer vision, aiming to localize a natural language query in a long, untrimmed video. It has a key role in the scientific community, in part due to the large amount of video generated every day. Although we find extensive work in this task, we note that research remains focused on a small selection of video representations, which may lead to architectural overfitting in the long run. To address this issue, we propose an empirical study to investigate the impact of different video features on a classical architecture. We extract features for three well-known benchmarks, Charades-STA, ActivityNet-Captions and YouCookII, using video encoders based on CNNs, temporal reasoning and transformers. Our results show significant differences in the performance of our model by simply changing the video encoder, while also revealing clear patterns and errors derived from the use of certain features, ultimately indicating potential feature complementarity.

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