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Methods/BezierAlign

BezierAlign

Computer VisionIntroduced 20003 papers
Source Paper

Description

BezierAlign is a feature sampling method for arbitrarily-shaped scene text recognition that exploits parameterization nature of a compact Bezier curve bounding box. Unlike RoIAlign, the shape of sampling grid of BezierAlign is not rectangular. Instead, each column of the arbitrarily-shaped grid is orthogonal to the Bezier curve boundary of the text. The sampling points have equidistant interval in width and height, respectively, which are bilinear interpolated with respect to the coordinates.

Formally given an input feature map and Bezier curve control points, we concurrently process all the output pixels of the rectangular output feature map with size h_out ×w_out h\_{\text {out }} \times w\_{\text {out }}h_out ×w_out . Taking pixel g_ig\_{i}g_i with position (g_iw,g_ih)\left(g\_{i w}, g\_{i h}\right)(g_iw,g_ih) (from output feature map) as an example, we calculate ttt by:

t=g_iww_outt=\frac{g\_{i w}}{w\_{o u t}}t=w_outg_iw​

We then calculate the point of upper Bezier curve boundary tptptp and lower Bezier curve boundary bpbpbp. Using tptptp and bpbpbp, we can linearly index the sampling point opopop by:

op=bp⋅g_ihh_out +tp⋅(1−g_ihh_out )op=bp \cdot \frac{g\_{i h}}{h\_{\text {out }}}+tp \cdot\left(1-\frac{g\_{i h}}{h\_{\text {out }}}\right)op=bp⋅h_out g_ih​+tp⋅(1−h_out g_ih​)

With the position of opopop, we can easily apply bilinear interpolation to calculate the result. Comparisons among previous sampling methods and BezierAlign are shown in the Figure.

Papers Using This Method

ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting2021-05-08DocBank: A Benchmark Dataset for Document Layout Analysis2020-06-01ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network2020-02-24