JSSFF: A Joint Structural-Semantic Fusion Framework for Remote Sensing Image Captioning
The encoder-decoder framework has become widely popular nowadays. In this model, the encoder extracts informative visual features from an input image, and the decoder employs a sequence-to-sequence formulation to generate the corresponding textual description from these features. The existing models focus more on the decision part. However, extracting meaningful information from the image can help the decoder generate an accurate caption by providing information about the objects and their relationship. Remote sensing images are highly complex. One major challenge is detecting objects that extend beyond their visible boundaries due to occlusion, overlapping structures, and unclear edges. ...
| Authors | Swadhin Das, Vivek Yadav |
|---|---|
| Primary category | cs.CV |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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