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Reported on 21 benchmarks across 4 tasks · 2 papers

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Miscellaneous12 results

Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@1· uses extra data· 2021-11-03
76.16
best: 84.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@10· uses extra data· 2021-11-03
96.82
best: 98.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@5· uses extra data· 2021-11-03
93.16
best: 96.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@1· uses extra data· 2021-11-03
57.08
best: 68 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@10· uses extra data· 2021-11-03
90.07
best: 92.8 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@5· uses extra data· 2021-11-03
82.66
best: 92.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@1· uses extra data· 2021-11-03
76.16
best: 84.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@10· uses extra data· 2021-11-03
96.82
best: 98.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@5· uses extra data· 2021-11-03
93.16
best: 96.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@1· uses extra data· 2021-11-03
57.08
best: 68 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@10· uses extra data· 2021-11-03
90.07
best: 92.8 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@5· uses extra data· 2021-11-03
82.66
best: 92.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387

Natural Language Processing6 results

Cross-Modal RetrievalonCOCO 2014
Image-to-text R@1· uses extra data· 2021-11-03
76.16
best: 84.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal RetrievalonCOCO 2014
Image-to-text R@10· uses extra data· 2021-11-03
96.82
best: 98.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal RetrievalonCOCO 2014
Image-to-text R@5· uses extra data· 2021-11-03
93.16
best: 96.5 (X2-VLM (large))
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@1· uses extra data· 2021-11-03
57.08
best: 68 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@10· uses extra data· 2021-11-03
90.07
best: 92.8 (VAST)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@5· uses extra data· 2021-11-03
82.66
best: 92.8 (BEiT-3)
An Empirical Study of Training End-to-End Vision-and-Language Transformers arXiv:2111.02387

Reasoning3 results

Visual ReasoningonWinoground
Group Score· 2023-03-25
12
best: 58.75 (GPT-4V (CoT, pick b/w two options))
Equivariant Similarity for Vision-Language Foundation Models arXiv:2303.14465
Visual ReasoningonWinoground
Image Score· 2023-03-25
15.75
best: 68.75 (GPT-4V (CoT, pick b/w two options))
Equivariant Similarity for Vision-Language Foundation Models arXiv:2303.14465
Visual ReasoningonWinoground
Text Score· 2023-03-25
39.25
best: 75.5 (GPT-4o + CA)
Equivariant Similarity for Vision-Language Foundation Models arXiv:2303.14465