VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of
Video-Language Models
- URL: http://arxiv.org/abs/2311.17404v1
- Date: Wed, 29 Nov 2023 07:15:34 GMT
- Title: VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of
Video-Language Models
- Authors: Shicheng Li, Lei Li, Shuhuai Ren, Yuanxin Liu, Yi Liu, Rundong Gao, Xu
Sun, Lu Hou
- Abstract summary: We present VITATECS, a diagnostic VIdeo-Text dAtaset for the evaluation of TEmporal Concept underStanding.
We first introduce a fine-grained taxonomy of temporal concepts in natural language in order to diagnose the capability of VidLMs to comprehend different temporal aspects.
We generate counterfactual video descriptions that differ from the original one only in the specified temporal aspect.
- Score: 28.455280591607686
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The ability to perceive how objects change over time is a crucial ingredient
in human intelligence. However, current benchmarks cannot faithfully reflect
the temporal understanding abilities of video-language models (VidLMs) due to
the existence of static visual shortcuts. To remedy this issue, we present
VITATECS, a diagnostic VIdeo-Text dAtaset for the evaluation of TEmporal
Concept underStanding. Specifically, we first introduce a fine-grained taxonomy
of temporal concepts in natural language in order to diagnose the capability of
VidLMs to comprehend different temporal aspects. Furthermore, to disentangle
the correlation between static and temporal information, we generate
counterfactual video descriptions that differ from the original one only in the
specified temporal aspect. We employ a semi-automatic data collection framework
using large language models and human-in-the-loop annotation to obtain
high-quality counterfactual descriptions efficiently. Evaluation of
representative video-language understanding models confirms their deficiency in
temporal understanding, revealing the need for greater emphasis on the temporal
elements in video-language research.
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