DCT-SwinGAN: Leveraging DCT and Swin Transformer for Face Synthesis from Sketch and Thermal Domains

Kotadiya, Haresh Kumar; Singh, Satish Kumar; Dubey, Shiv Ram; Yadav, Nand Kumar

doi:10.1007/978-3-031-58174-8_20

Communications in Computer and Information Science

2024

DOI: 10.1007/978-3-031-58174-8_20

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DCT-SwinGAN: Leveraging DCT and Swin Transformer for Face Synthesis from Sketch and Thermal Domains

Haresh Kumar Kotadiya,

Satish Kumar Singh,

Shiv Ram Dubey

et al.

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Toward identity preserving in face sketch-photo synthesis using a hybrid CNN-Mamba framework

Tang,

Jiang,

Wang

et al. 2024

Sci Rep

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The synthesis of facial sketch-photo has important applications in practical life, such as crime investigation. Many convolutional neural networks (CNNs) based methods have been proposed to address this issue. However, due to the substantial modal differences between sketch and photo, the CNN’s insensitivity to global information, and insufficient utilization of hierarchical features, synthesized photos struggle to balance both identity preservation and image quality. Recently, State Space Sequence Models (SSMs) have achieved exciting results in computer vision (CV) tasks. Inspired by SSMs, we design a hybrid CNN–SSM model called FaceMamba for the Face Sketch-Photo Synthesis (FSPS) task. It includes an original Face Vision Mamba Attention for modeling in latent space using SSM. Additionally, it incorporates a general auxiliary method called Attention Feature Injection that combines encoding features, decoding features, and external auxiliary features using attention mechanisms. FaceMamba combines Mamba’s modeling ability for long-range dependencies with CNN’s powerful local feature extraction ability, and utilizes hierarchical features at the appropriate position. Adequate experimental and evaluation results reveal that FaceMamba has strong competitiveness in FSPS task, achieving the best balance between identity preservation and image quality.

show abstract

Toward identity preserving in face sketch-photo synthesis using a hybrid CNN-Mamba framework

Tang,

Jiang,

Wang

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

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DCT-SwinGAN: Leveraging DCT and Swin Transformer for Face Synthesis from Sketch and Thermal Domains

Cited by 1 publication

References 26 publications

Toward identity preserving in face sketch-photo synthesis using a hybrid CNN-Mamba framework

Toward identity preserving in face sketch-photo synthesis using a hybrid CNN-Mamba framework

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