4 accepted papers
Pre-trained Visual-Language Models (VLMs) have demonstrated powerful performance on various downstream tasks. Recently, many prompt tuning methods represented by Context Optimization (CoOp) have effectively adapted VLMs to few-shot tasks. However, the CoOp-based methods suffer from overfitting to ba…
In the automatic driving 3D object detection task, the multi-modal fusion method can realize the complementarity of different modal information, especially the fusion algorithm of LiDAR point cloud and camera image has been widely used. Nowadays, most point cloud-image fusion methods employ external
Synthetic aperture radar (SAR) has gradually demonstrated its advantages in a variety of application fields. However, due to the complexity of the background, the simplicity of the texture, and the multi-scale of the target, object detection in large-scale SAR images is still a major challenge. This…
The recent advance has shown that few-shot learning may be a promising way to alleviate the data reliance of remote sensing image scene classification. However, most existing works focus on extracting distinguishable features only from visual modality, while the problem of learning knowledge from mu…