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
Descriptive Caption Enhancement with Visual Specialists for Multimodal Perception
Yanpeng Sun, Jing Hao, Ke Zhu, Jiang-Jiang Liu, Yuxiang Zhao, Xiaofan Li, Gang Zhang, Zechao Li, Jingdong Wang
G-VEval: A Versatile Metric for Evaluating Image and Video Captions Using GPT-4o
Tony Cheng Tong, Sirui He, Zhiwen Shao, Dit-Yan Yeung