# Progressive Scale-aware Network for Remote sensing Image Change Captioning

arXiv: https://arxiv.org/abs/2303.00355 · HTML: https://mlsanity.com/paper/2303.00355/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 13 references that are in the map.
- First posted on arXiv 1 Mar 2023.

## Builds on (most cited first, 4 of 4)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [Describing and Localizing Multiple Changes with Transformers](https://mlsanity.com/paper/2103.14146/) (2021)

## Built on by (most cited first, 27 of 27)

- [Change-Agent: Towards Interactive Comprehensive Remote Sensing Change Interpretation and Analysis](https://mlsanity.com/paper/2403.19646/) (2024)
- [Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Model](https://mlsanity.com/paper/2501.00895/) (2025)
- [Changes to Captions: An Attentive Network for Remote Sensing Change Captioning](https://mlsanity.com/paper/2304.01091/) (2023)
- [RSCaMa: Remote Sensing Image Change Captioning with State Space Model](https://mlsanity.com/paper/2404.18895/) (2024)
- [ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuning](https://mlsanity.com/paper/2409.08582/) (2024)
- [Semantic-CC: Boosting Remote Sensing Image Change Captioning via Foundational Knowledge and Semantic Guidance](https://mlsanity.com/paper/2407.14032/) (2024)
- [Enhancing Perception of Key Changes in Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2409.12612/) (2024)
- [Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change Captioning](https://mlsanity.com/paper/2312.15311/) (2023)
- [A Lightweight Sparse Focus Transformer for Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2405.06598/) (2024)
- [Mask Approximation Net: A Novel Diffusion Model Approach for Remote Sensing Change Captioning](https://mlsanity.com/paper/2412.19179/) (2024)
- [Context-aware Difference Distilling for Multi-change Captioning](https://mlsanity.com/paper/2405.20810/) (2024)
- [Robust Change Captioning in Remote Sensing: SECOND-CC Dataset and MModalCC Framework](https://mlsanity.com/paper/2501.10075/) (2025)
- [ChangeMinds: Multi-task Framework for Detecting and Describing Changes in Remote Sensing](https://mlsanity.com/paper/2410.10047/) (2024)
- [BTCChat: Advancing Remote Sensing Bi-temporal Change Captioning with Multimodal Large Language Model](https://mlsanity.com/paper/2509.05895/) (2025)
- [DeltaVLM: Interactive Remote Sensing Image Change Analysis via Instruction-guided Difference Perception](https://mlsanity.com/paper/2507.22346/) (2025)
- [Multi-view Remote Sensing Image Segmentation With SAM priors](https://mlsanity.com/paper/2405.14171/) (2024)
- [Viewpoint Integration and Registration with Vision Language Foundation Model for Image Change Understanding](https://mlsanity.com/paper/2309.08585/) (2023)
- [MV-CC: Mask Enhanced Video Model for Remote Sensing Change Caption](https://mlsanity.com/paper/2410.23946/) (2024)
- [Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation](https://mlsanity.com/paper/2412.15939/) (2024)
- [SAM Guided Semantic and Motion Changed Region Mining for Remote Sensing Change Captioning](https://mlsanity.com/paper/2511.21420/) (2025)
- [DFM: Difference Feature Modeling with Text-Guided Gated Contrastive Loss for Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2606.27410/) (2026)
- [RSICCLLM: A Multimodal Large Language Model for Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2606.28266/) (2026)
- [UAV as Urban Construction Change Monitor: A New Benchmark and Change Captioning Model](https://mlsanity.com/paper/2605.04409/) (2026)
- [HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2605.15024/) (2026)
- [Stateful Visual Encoders for Vision-Language Models](https://mlsanity.com/paper/2606.04433/) (2026)
- [LBTCap: A Lightweight Bilateral Transformer for Real-Time Remote Sensing Image Change Captioning](https://mlsanity.com/paper/2607.03320/) (2026)
- [MGRL-RSCC: Multi-Granularity Reward Reinforcement Learning for Fine-Grained Remote Sensing Change Captioning](https://mlsanity.com/paper/2609.26166/) (2026)

## Abstract (arXiv)

Remote sensing (RS) images contain numerous objects of different scales, which poses significant challenges for the RS image change captioning (RSICC) task to identify visual changes of interest in complex scenes and describe them via language. However, current methods still have some weaknesses in sufficiently extracting and utilizing multi-scale information. In this paper, we propose a progressive scale-aware network (PSNet) to address the problem. PSNet is a pure Transformer-based model. To sufficiently extract multi-scale visual features, multiple progressive difference perception (PDP) layers are stacked to progressively exploit the differencing features of bitemporal features. To sufficiently utilize the extracted multi-scale features for captioning, we propose a scale-aware reinforcement (SR) module and combine it with the Transformer decoding layer to progressively utilize the features from different PDP layers. Experiments show that the PDP layer and SR module are effective and our PSNet outperforms previous methods. Our code is public at https://github.com/Chen-Yang-Liu/PSNet