Image Captioning
Image captioning aims to automatically generate descriptive text for images, bridging the gap between computer vision and natural language processing. Current research focuses on improving efficiency (e.g., through early exits and knowledge distillation), enhancing performance on fine-grained datasets (e.g., by incorporating object-part details), and developing more robust evaluation metrics (e.g., addressing hallucinations). These advancements are significant for applications ranging from assisting visually impaired individuals to improving image search and retrieval, and are driving innovation in both vision-language models and evaluation methodologies.
Papers
Controllable Contextualized Image Captioning: Directing the Visual Narrative through User-Defined Highlights
Shunqi Mao, Chaoyi Zhang, Hang Su, Hwanjun Song, Igor Shalyminov, Weidong Cai
CIC-BART-SSA: Controllable Image Captioning with Structured Semantic Augmentation
Kalliopi Basioti, Mohamed A. Abdelsalam, Federico Fancellu, Vladimir Pavlovic, Afsaneh Fazly