Pattern recognition (psychology)

Operating system

Inference

Political science

Politics

Computer science

Gene

Philosophy

Set (abstract data type)

Representation (politics)

Computer vision

Biochemistry

Linguistics

Redundancy (engineering)

Feature (linguistics)

ENCODE

Artificial intelligence

Code (set theory)

Encoding (memory)

Chemistry

Programming language

Segmentation

Image segmentation

BiSeNet [28], [27] has been proved to be a popular two-stream network for real-time segmentation. However, its principle of adding an extra path to encode spatial information is time-consuming, and the backbones borrowed from pretrained tasks, e.g., image classification, may be inefficient for image segmentation due to the deficiency of task-specific design. To handle these problems, we propose a novel and efficient structure named Short-Term Dense Concatenate network (STDC network) by removing structure redundancy. Specifically, we gradually reduce the dimension of feature maps and use the aggregation of them for image representation, which forms the basic module of STDC network. In the decoder, we propose a Detail Aggregation module by integrating the learning of spatial information into low-level layers in single-stream manner. Finally, the low-level features and deep features are fused to predict the final segmentation results. Extensive experiments on Cityscapes and CamVid dataset demonstrate the effecti...

Rethinking BiSeNet For Real-time Semantic Segmentation