Nov 20, 2014 · Our simple metric captures human judgment of consensus better than existing metrics across sentences generated by various sources. We also evaluate five state-of-the-art image description approaches using this new protocol and provide a …

Mar 22, 2022 · I see that CIDEr is a universal metric in Image Captioning. I want to use this metric on my project, but I can't find any library. There is few info. CIDEr can only be seen in paper. And I can have searched just BLUE library which is used to …

Our simple metric captures human judgment of consensus better than existing metrics across sentences generated by various sources. We also evaluate five state-of-the-art image description approaches using this new protocol and provide a benchmark for future comparisons.

Our simple metric captures human judgment of consensus better than exist-ing metrics across sentences generated by various sources. We also evaluate five state-of-the-art image description ap-proaches using this new protocol and provide a benchmark for future comparisons.

Evaluation code for CIDEr metric. Provides CIDEr as well as CIDEr-D (CIDEr Defended) which is more robust to gaming effects.

Mar 15, 2024 · The CIDEr metric measures the similarity between a generated caption and the reference captions, and it is based on the concept of consensus: the idea that good captions should not only be similar to the reference captions in terms of word choice and grammar, but also in terms of meaning and content.

The CIDEr (Consensus-based Image Description Evaluation) metric is widely used in image captioning tasks to evaluate the quality of generated captions. The metric assesses how well the generated caption aligns with human-written reference captions by considering both the frequency and relevance of words or phrases.

We introduce an annotation modality for measuring consensus, a metric CIDEr for automatically computing consensus, and two datasets, PASCAL-50S and ABSTRACT-50S with 50 sentences per image. We demonstrate CIDEr has improved accuracy over existing metrics for …

Nov 20, 2014 · This paradigm consists of three main parts: a new triplet-based method of collecting human annotations to measure consensus, a new automated metric (CIDEr) that captures consensus, and two new datasets: PASCAL-50S and ABSTRACT-50S that contain 50 sentences describing each image.

Our simple metric captures human judgment of consensus better than exist-ing metrics across sentences generated by various sources. We also evaluate five state-of-the-art image description ap-proaches using this new protocol and provide a benchmark for future comparisons.