arXiv:2301.08784
공식 코드 · Papers with Code
Visual Semantic Relatedness Dataset for Image Captioning
원문 초록
Modern image captioning system relies heavily on extracting knowledge from images to capture the concept of a static story. In this paper, we propose a textual visual context dataset for captioning, in which the publicly available dataset COCO Captions (Lin et al., 2014) has been extended with information about the scene (such as objects in the image). Since this information has a textual form, it can be used to leverage any NLP task, such as text similarity or semantic relation methods, into captioning systems, either as an end-to-end training strategy or a post-processing based approach.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Redemption Score: An Evaluation Framework to Rank Image Captions While Redeeming Image Semantics and Language Pragmatics
Unleashing Text-to-Image Diffusion Prior for Zero-Shot Image Captioning
Bridging Paintings and Music -- Exploring Emotion based Music Generation through Paintings
ActAlign: Zero-Shot Fine-Grained Video Classification via Language-Guided Sequence Alignment
Adding simple structure at inference improves Vision-Language Compositionality
Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.