AI Chat AI Image Generator AI Video Text to Speech

StyleM: Stylized Metrics for Image Captioning Built with Contrastive N-grams

01/04/2022
∙
by   Chengxi Li, et al.
∙
0
∙

In this paper, we build two automatic evaluation metrics for evaluating the association between a machine-generated caption and a ground truth stylized caption: OnlyStyle and StyleCIDEr.

READ FULL TEXT

Related Research

research
∙ 09/05/2019

REO-Relevance, Extraness, Omission: A Fine-grained Evaluation for Image Captioning

Popular metrics used for evaluating image captioning systems, such as BL...
0 Ming Jiang, et al. ∙
research
∙ 08/27/2020

A Survey of Evaluation Metrics Used for NLG Systems

The success of Deep Learning has created a surge in interest in a wide a...
0 Ananya B. Sai, et al. ∙
research
∙ 09/30/2020

Teacher-Critical Training Strategies for Image Captioning

Existing image captioning models are usually trained by cross-entropy (X...
0 Yiqing Huang, et al. ∙
research
∙ 06/29/2021

Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder

Automatically evaluating the quality of image captions can be very chall...
0 Chao Zeng, et al. ∙
research
∙ 05/24/2023

Gender Biases in Automatic Evaluation Metrics: A Case Study on Image Captioning

Pretrained model-based evaluation metrics have demonstrated strong perfo...
0 Haoyi Qiu, et al. ∙
research
∙ 10/06/2021

Is An Image Worth Five Sentences? A New Look into Semantics for Image-Text Matching

The task of image-text matching aims to map representations from differe...
0 Ali Furkan Biten, et al. ∙
research
∙ 10/26/2020

Curious Case of Language Generation Evaluation Metrics: A Cautionary Tale

Automatic evaluation of language generation systems is a well-studied pr...
0 Ozan Caglayan, et al. ∙

Please sign up or login with your details

Forgot password? Click here to reset

Out of credits

Refill your membership to continue using DeepAI

Stripe
Paypal