| Paper info | Key elements | 
|---|---|
| > Learning Independent Instance Maps for Crowd Localization(IIM) | > Rounded line arrow(圆角折线箭头) | 
| > Changes to Captions: An Attentive Network for Remote Sensing Change Captioning | > Partitioned cube(分块立方体) | 
| > Attention Is All You Need | >Custom curved arrow(自定义弯曲箭头) | 
| > Image Captioning with Deep Bidirectional LSTMs | |
| > EVCAP Retrieval-Augmented Image Captioning with External Visual-Name Memory for Open-World Comprehension | > Vector icon(矢量图标) | 
| > Few-shot Oriented Object Detection with Memorable Contrastive Learning in Remote Sensing Images | > Thin rectangle(薄长方体) | 
| > Transferable Decoding with Visual Entities for Zero-Shot Image Captioning | |
| >UP-Diff Latent Diffusion Model for Remote Sensing Urban Prediction | > Judge the arrow is straight or not(判断箭头笔直与否) | 
| >GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature-Guided DDPM | > Any shape polygon(任意形状多边形) | 
| >GCD-DDPM: Language-only Efficient Training of Zero-shot Composed Image Retrieval | |
| >Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models | > Half curved rectangle(半曲线矩形) | 
| >From Association to Generation: Text-only Captioning by Unsupervised Cross-modal Mapping | > Merge shapes(合并形状) | 
| >KIND: Knowledge Integration and Diversion in Diffusion Models | > Color box(彩色方块) | 
| >Single-Stream Extractor Network With Contrastive Pre-Training for Remote-Sensing Change Captioning | |
| >Diffusion-RSCC: Diffusion Probabilistic Model for Change Captioning in Remote Sensing Images | > 立方体阴影、平面堆叠正方形 | 
| >CaLa: Complementary Association Learning for Augmenting Composed Image Retrieval | > islide(PPT插件) | 
| >Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image Segmentation | > 均匀分布、堆叠矩形 | 
| >MeTA: Multi-source Test Time Adaptation | > 不同曲线的选用和坐标轴设置 | 
| >Teaching CLIP to Count to Ten | 
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