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SOTA
场景文本识别
Scene Text Recognition On Ic19 Art
Scene Text Recognition On Ic19 Art
评估指标
Accuracy (%)
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy (%)
Paper Title
CLIP4STR-L (DataComp-1B)
86.4
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-L
85.9
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-B
85.8
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
MGP-STR
85.5
Multi-Granularity Prediction for Scene Text Recognition
PARSeq
84.5±0.1
Scene Text Recognition with Permuted Autoregressive Sequence Models
0 of 5 row(s) selected.
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HyperAI
HyperAI超神经
首页
算力平台
文档
资讯
论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
服务条款
隐私政策
中文
HyperAI
HyperAI超神经
Toggle Sidebar
全站搜索…
⌘
K
Command Palette
Search for a command to run...
算力平台
首页
SOTA
场景文本识别
Scene Text Recognition On Ic19 Art
Scene Text Recognition On Ic19 Art
评估指标
Accuracy (%)
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy (%)
Paper Title
CLIP4STR-L (DataComp-1B)
86.4
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-L
85.9
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
CLIP4STR-B
85.8
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
MGP-STR
85.5
Multi-Granularity Prediction for Scene Text Recognition
PARSeq
84.5±0.1
Scene Text Recognition with Permuted Autoregressive Sequence Models
0 of 5 row(s) selected.
Previous
Next