FastTab combines a Tiny Recursive Module and axial 1D Transformer encoders to predict table grids, headers, and cell spans directly, achieving competitive accuracy on four benchmarks with low-latency inference.
SEMv2: table separation line detection based on condi- tional convolution.CoRR, abs/2303.04384
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TableSeq unifies table structure recognition, content extraction, and cell localization by generating an interleaved autoregressive sequence of HTML tags, cell text, and discretized coordinate tokens from an input image.
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FastTab: A Fast Table Recognizer with a Tiny Recursive Module and 1D Transformers
FastTab combines a Tiny Recursive Module and axial 1D Transformer encoders to predict table grids, headers, and cell spans directly, achieving competitive accuracy on four benchmarks with low-latency inference.
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TableSeq: Unified Generation of Structure, Content, and Layout
TableSeq unifies table structure recognition, content extraction, and cell localization by generating an interleaved autoregressive sequence of HTML tags, cell text, and discretized coordinate tokens from an input image.