mlsanityData to 7 Oct 2026

VIFIDEL: Evaluating the Visual Fidelity of Image Descriptions

arXiv 1907.09340 ↗First posted 22 Jul 2019cs.CL cs.CV cs.LGcited by 21

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Abstract (arXiv)

We address the task of evaluating image description generation systems. We propose a novel image-aware metric for this task: VIFIDEL. It estimates the faithfulness of a generated caption with respect to the content of the actual image, based on the semantic similarity between labels of objects depicted in images and words in the description. The metric is also able to take into account the relative importance of objects mentioned in human reference descriptions during evaluation. Even if these human reference descriptions are not available, VIFIDEL can still reliably evaluate system descriptions. The metric achieves high correlation with human judgments on two well-known datasets and is competitive with metrics that depend on human references

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jul 2019.

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Citing papers per year: 2021: 5; 2022: 1; 2023: 5; 2024: 5; 2025: 5.

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  1. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
  2. 2023Aligning Text-to-Image Models using Human Feedbackcited by 418
  3. 2021VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomenacited by 134
  4. 2021UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learningcited by 37
  5. 2023ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Modelscited by 26
  6. 2023Mitigating Open-Vocabulary Caption Hallucinationscited by 18
  7. 2024A Survey on Quality Metrics for Text-to-Image Generationcited by 17
  8. 2021COSMic: A Coherence-Aware Generation Metric for Image Descriptionscited by 9
  9. 2024Text-to-Image Synthesis: A Decade Surveycited by 9
  10. 2025Reference-free Evaluation Metrics for Text Generation: A Surveycited by 9
  11. 2024CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smellscited by 8
  12. 2023Multimodal Data Augmentation for Image Captioning using Diffusion Modelscited by 6
9 more
  1. 2023PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioningcited by 5
  2. 2022Paraphrasing Is All You Need for Novel Object Captioningcited by 4
  3. 2025VC-Inspector: Advancing Reference-free Evaluation of Video Captions with Factual Analysiscited by 4
  4. 2021Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encodercited by 0
  5. 2024ICC: Quantifying Image Caption Concreteness for Multimodal Dataset Curationcited by 0
  6. 2024Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy, Trends and Metrics Analysiscited by 0
  7. 2025Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logiccited by 0
  8. 2025On Explaining Visual Captioning with Hybrid Markov Logic Networkscited by 0
  9. 2025Believing without Seeing: Quality Scores for Contextualizing Vision-Language Model Explanationscited by 0