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An end-to-end trainable (fully differentiable) method for multi-language scene text localization and recognition is proposed. The approach is based on a single fully convolutional network (FCN) with shared layers for both tasks. E2E-MLT is the first published multi-language OCR for scene text. While trained in multi-language setup, E2E-MLT demonstrates competitive performance when compared to other methods trained for English scene text alone. The experiments show that obtaining accurate multi-language multi-script annotations is a challenging problem.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1801.09919")
get_code_for_paper("1801.09919")
have("1801.09919")
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