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Models/VSE-Gradient

VSE-Gradient

Reported on 36 benchmarks across 3 tasks · 1 paper

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

Miscellaneous24 results

Image Retrieval with Multi-Modal QueryonFlickr30k
Image-to-text R@1· uses extra data· 2022-10-21
97
best: 98.8 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonFlickr30k
Image-to-text R@10· uses extra data· 2022-10-21
100
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonFlickr30k
Image-to-text R@5· uses extra data· 2022-10-21
99.6
best: 100 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonFlickr30k
Text-to-image R@1· uses extra data· 2022-10-21
86.3
best: 93.3 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonFlickr30k
Text-to-image R@10· uses extra data· 2022-10-21
99
best: 99.8 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonFlickr30k
Text-to-image R@5· uses extra data· 2022-10-21
97.4
best: 99.5 (M2-Encoder)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@1· uses extra data· 2022-10-21
81.4
best: 84.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@10· uses extra data· 2022-10-21
97.9
best: 98.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Image-to-text R@5· uses extra data· 2022-10-21
95.6
best: 96.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@1· uses extra data· 2022-10-21
63.6
best: 68 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@10· uses extra data· 2022-10-21
91.5
best: 92.8 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Image Retrieval with Multi-Modal QueryonCOCO 2014
Text-to-image R@5· uses extra data· 2022-10-21
86
best: 92.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Image-to-text R@1· uses extra data· 2022-10-21
97
best: 98.8 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Image-to-text R@10· uses extra data· 2022-10-21
100
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Image-to-text R@5· uses extra data· 2022-10-21
99.6
best: 100 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Text-to-image R@1· uses extra data· 2022-10-21
86.3
best: 93.3 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Text-to-image R@10· uses extra data· 2022-10-21
99
best: 99.8 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonFlickr30k
Text-to-image R@5· uses extra data· 2022-10-21
97.4
best: 99.4 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@1· uses extra data· 2022-10-21
81.4
best: 84.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@10· uses extra data· 2022-10-21
97.9
best: 98.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Image-to-text R@5· uses extra data· 2022-10-21
95.6
best: 96.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@1· uses extra data· 2022-10-21
63.6
best: 68 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@10· uses extra data· 2022-10-21
91.5
best: 92.8 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal Information RetrievalonCOCO 2014
Text-to-image R@5· uses extra data· 2022-10-21
86
best: 92.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188

Natural Language Processing12 results

Cross-Modal RetrievalonFlickr30k
Image-to-text R@1· uses extra data· 2022-10-21
97
best: 98.8 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonFlickr30k
Image-to-text R@10· uses extra data· 2022-10-21
100
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonFlickr30k
Image-to-text R@5· uses extra data· 2022-10-21
99.6
best: 100 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonFlickr30k
Text-to-image R@1· uses extra data· 2022-10-21
86.3
best: 93.3 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonFlickr30k
Text-to-image R@10· uses extra data· 2022-10-21
99
best: 99.8 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonFlickr30k
Text-to-image R@5· uses extra data· 2022-10-21
97.4
best: 99.4 (ERNIE-ViL 2.0)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Image-to-text R@1· uses extra data· 2022-10-21
81.4
best: 84.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Image-to-text R@10· uses extra data· 2022-10-21
97.9
best: 98.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Image-to-text R@5· uses extra data· 2022-10-21
95.6
best: 96.5 (X2-VLM (large))
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@1· uses extra data· 2022-10-21
63.6
best: 68 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@10· uses extra data· 2022-10-21
91.5
best: 92.8 (VAST)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188
Cross-Modal RetrievalonCOCO 2014
Text-to-image R@5· uses extra data· 2022-10-21
86
best: 92.8 (BEiT-3)
Dissecting Deep Metric Learning Losses for Image-Text Retrieval arXiv:2210.13188