# What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images

Source: [What Time Tells Us? An Explorative Study of Time Awareness Learned from Static Images](<https://www.sota2.com/research/paper/68fa77901e209131cea73ec8>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-11-08T05:01:25.623Z

Authors: Dongheng Lin, Han Hu, Jianbo Jiao

Published: 2025-03-23T01:56:35.000Z

## Abstract

Time becomes visible through illumination changes in what we see. Inspired by this, in this paper we explore the potential to learn time awareness from static images, trying to answer: \*what time tells us?\* To this end, we first introduce a Time-Oriented Collection (TOC) dataset, which contains 130,906 images with reliable timestamps. Leveraging this dataset, we propose a Time-Image Contrastive Learning (TICL) approach to jointly model timestamps and related visual representations through cross-modal contrastive learning. We found that the proposed TICL, 1) not only achieves state-of-the-art performance on the timestamp estimation task, over various benchmark metrics, 2) but also, interestingly, though only seeing static images, the time-aware embeddings learned from TICL show strong capability in several time-aware downstream tasks such as time-based image retrieval, video scene classification, and time-aware image editing. Our findings suggest that time-related visual cues can be learned from static images and are beneficial for various vision tasks, laying a foundation for future research on understanding time-related visual context. Project page: https://rathgrith.github.io/timetells\_release/

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Time prediction on TIGeR 86k (test)](<https://www.sota2.com/research/sota/time-prediction-on-tiger-86k-test.md>): Time Prediction; TIGeR 86k (test); ToY Error: 59.88.

- [Time prediction on CVT (test)](<https://www.sota2.com/research/sota/time-prediction-on-cvt-test.md>): Time Prediction; CVT (test); ToY Error: 72.63.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2503.17899>)

[PDF](<https://arxiv.org/pdf/2503.17899.pdf>)