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Models/CLIP4STR-L (DataComp-1B)

CLIP4STR-L (DataComp-1B)

Reported on 27 benchmarks across 3 tasks · 1 paper · 18 SOTA

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

Computer Vision18 results

Scene ParsingonCUTE80
Accuracy· uses extra data· 2023-05-23
99.7
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonUber-Text
Accuracy (%)· 2023-05-23
92.2
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonIC19-Art
Accuracy (%)· 2023-05-23
86.4
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonICDAR2015
Accuracy· 2023-05-23
91.4
best: 93.5 (DTrOCR 105M)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonIIIT5k
Accuracy· uses extra data· 2023-05-23
99.6
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonICDAR2013
Accuracy· 2023-05-23
99
best: 99.42 (CLIP4STR-L*)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononCUTE80
Accuracy· uses extra data· 2023-05-23
99.7
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononUber-Text
Accuracy (%)· 2023-05-23
92.2
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononIC19-Art
Accuracy (%)· 2023-05-23
86.4
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononICDAR2015
Accuracy· 2023-05-23
91.4
best: 93.5 (DTrOCR 105M)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononIIIT5k
Accuracy· uses extra data· 2023-05-23
99.6
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononICDAR2013
Accuracy· 2023-05-23
99
best: 99.42 (CLIP4STR-L*)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonSVT
Accuracy· uses extra data· 2023-05-23
98.6
best: 99.1 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonSVTP
Accuracy· 2023-05-23
98.1
best: 98.6 (DTrOCR 105M)
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene ParsingonWOST
1:1 Accuracy· uses extra data· 2023-05-23
90.6
best: 90.9 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononSVT
Accuracy· uses extra data· 2023-05-23
98.6
best: 99.1 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononSVTP
Accuracy· 2023-05-23
98.1
best: 98.6 (DTrOCR 105M)
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
Scene Text RecognitiononWOST
1:1 Accuracy· uses extra data· 2023-05-23
90.6
best: 90.9 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014

Audio9 results

2D Semantic SegmentationonCUTE80
Accuracy· uses extra data· 2023-05-23
99.7
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonUber-Text
Accuracy (%)· 2023-05-23
92.2
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonIC19-Art
Accuracy (%)· 2023-05-23
86.4
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonICDAR2015
Accuracy· 2023-05-23
91.4
best: 93.5 (DTrOCR 105M)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonIIIT5k
Accuracy· uses extra data· 2023-05-23
99.6
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonICDAR2013
Accuracy· 2023-05-23
99
best: 99.42 (CLIP4STR-L*)
SOTA
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonSVT
Accuracy· uses extra data· 2023-05-23
98.6
best: 99.1 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonSVTP
Accuracy· 2023-05-23
98.1
best: 98.6 (DTrOCR 105M)
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014
2D Semantic SegmentationonWOST
1:1 Accuracy· uses extra data· 2023-05-23
90.6
best: 90.9 (CLIP4STR-H (DFN-5B))
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model arXiv:2305.14014