# Change Detection Meets Visual Question Answering Source: [Change Detection Meets Visual Question Answering]() Collection index: [llms.txt]() Data updated: 2025-10-26T00:50:11.375Z Authors: Zhenghang Yuan, Lichao Mou, Zhitong Xiong, Xiaoxiang Zhu Published: 2021-12-12T22:39:20.000Z ## Abstract The Earth's surface is continually changing, and identifying changes plays an important role in urban planning and sustainability. Although change detection techniques have been successfully developed for many years, these techniques are still limited to experts and facilitators in related fields. In order to provide every user with flexible access to change information and help them better understand land-cover changes, we introduce a novel task: change detection-based visual question answering (CDVQA) on multi-temporal aerial images. In particular, multi-temporal images can be queried to obtain high level change-based information according to content changes between two input images. We first build a CDVQA dataset including multi-temporal image-question-answer triplets using an automatic question-answer generation method. Then, a baseline CDVQA framework is devised in this work, and it contains four parts: multi-temporal feature encoding, multi-temporal fusion, multi-modal fusion, and answer prediction. In addition, we also introduce a change enhancing module to multi-temporal feature encoding, aiming at incorporating more change-related information. Finally, effects of different backbones and multi-temporal fusion strategies are studied on the performance of CDVQA task. The experimental results provide useful insights for developing better CDVQA models, which are important for future research on this task. ## 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. - [Change-Detection-based Visual Question Answering on QAG-360K (test)](): Change-Detection-based Visual Question Answering; QAG-360K (test); CN: 82.25. - [Change Visual Question Answering on CDVQA (test 1)](): Change Visual Question Answering; CDVQA (test 1); AA: 55.3. - [Change Visual Question Answering on CDVQA (test2)](): Change Visual Question Answering; CDVQA (test2); AA: 55.4. ## Original sources and implementation [Original paper]() [PDF]()