Jixiang Shi, Jin Liu, Wen Lu, Ruisen Liu, Jiajun Wang
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HFINet: Heteroscale feature integration network for real-time semantic segmentation
Effectively segmenting visual images from a semantic perspective remains an under-explored research issue. The absence of heteroscale recognition leads to persistent challenges in accurately delineating boundaries, particularly for small and slender objects next to larger ones. Existing semantic segmentation methods suffer from spatial resolution loss in downsampling, which smooths out high-frequency features and blurs object boundaries, resulting in the missegmentation of smaller objects. To address this, a novel boundary branch is proposed in our multilateral network. It incorporates spatial integration and channel significance to integrate heteroscale features, mitigating missegmentation and utilizing boundary loss to enhance the learning process, thereby improving the model’s robustness in complex scenes. Additionally, the aggregation pyramid pooling module fuses contextual information from low-resolution feature maps to enlarge the receptive field, achieving greater semantic label accuracy. Experimental results of our proposed HFINet demonstrate that integrating boundary features significantly improves segmentation accuracy, particularly for precise object boundary delineation. This work offers a promising direction for enhancing the robustness of semantic segmentation models in challenging scenarios involving complex object boundaries.
期刊介绍:
Signal Processing: Image Communication is an international journal for the development of the theory and practice of image communication. Its primary objectives are the following:
To present a forum for the advancement of theory and practice of image communication.
To stimulate cross-fertilization between areas similar in nature which have traditionally been separated, for example, various aspects of visual communications and information systems.
To contribute to a rapid information exchange between the industrial and academic environments.
The editorial policy and the technical content of the journal are the responsibility of the Editor-in-Chief, the Area Editors and the Advisory Editors. The Journal is self-supporting from subscription income and contains a minimum amount of advertisements. Advertisements are subject to the prior approval of the Editor-in-Chief. The journal welcomes contributions from every country in the world.
Signal Processing: Image Communication publishes articles relating to aspects of the design, implementation and use of image communication systems. The journal features original research work, tutorial and review articles, and accounts of practical developments.
Subjects of interest include image/video coding, 3D video representations and compression, 3D graphics and animation compression, HDTV and 3DTV systems, video adaptation, video over IP, peer-to-peer video networking, interactive visual communication, multi-user video conferencing, wireless video broadcasting and communication, visual surveillance, 2D and 3D image/video quality measures, pre/post processing, video restoration and super-resolution, multi-camera video analysis, motion analysis, content-based image/video indexing and retrieval, face and gesture processing, video synthesis, 2D and 3D image/video acquisition and display technologies, architectures for image/video processing and communication.