The proposed method fuses gradient magnitude and direction coherence of text pixels in a new way for detecting candidate regions.
In addition, we used an Adaptive channel reducing the domain gap between synthetic and real night images, which also complements the failures of Real channel output.
In this paper, we propose a noveldeep architecture, NiSeNet, that performs semantic segmen-tation of night scenes using a domain mapping approach ofsynthetic to real data.
Ranked #1 on Semantic Segmentation on BDD100K
Facial micro-expressions are sudden involuntary minute muscle movements which reveal true emotions that people try to conceal.
For each line segment, the proposed method estimates angle and length, which gives a point in polar domain.
Regional language extraction from a natural scene image is always a challenging proposition due to its dependence on the text information extracted from Image.