Freezing partial source representations matters for image inpainting under limited data

Zhang, Yanbing; Yang, Mengping; Xiao, Ting; Wang, Zhe; Chi, Ziqiu

doi:10.1016/j.engappai.2024.108072

Engineering Applications of Artificial Intelligence

2024

DOI: 10.1016/j.engappai.2024.108072

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Freezing partial source representations matters for image inpainting under limited data

Yanbing Zhang,

Mengping Yang,

Ting Xiao

et al.

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Cited by 3 publications

References 43 publications

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Unified Domain Adaptation for Specialized Indoor Scene Inpainting Using a Pre-Trained Model

Akter,

Lee

2024

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Image inpainting for indoor environments presents unique challenges due to complex spatial relationships, diverse lighting conditions, and domain-specific object configurations. This paper introduces a resource-efficient post-processing framework that enhances domain-specific image inpainting through an adaptation mechanism. Our architecture integrates a convolutional neural network with residual connections optimized via a multi-term objective function combining perceptual losses and adaptive loss weighting. Experiments on our curated dataset of 4000 indoor household scenes demonstrate improved performance, with training completed in 20 min on commodity GPU hardware with 0.14 s of inference latency per image. The framework exhibits enhanced results across standard metrics (FID, SSIM, LPIPS, MAE, and PSNR), showing improvements in structural coherence and perceptual quality while preserving cross-domain generalization abilities. Our methodology offers a novel approach for efficient domain adaptation in image inpainting, particularly suitable for real-world applications under computational constraints. This work advances the development of domain-aware image restoration systems and provides architectural insights for specialized image processing frameworks.

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Freezing partial source representations matters for image inpainting under limited data

Cited by 3 publications

References 43 publications

Hybrid rotation self-supervision and feature space normalization for class incremental learning

Hybrid rotation self-supervision and feature space normalization for class incremental learning

Target-Focused Enhancement Network for Distant Infrared Dim and Small Target Detection

Unified Domain Adaptation for Specialized Indoor Scene Inpainting Using a Pre-Trained Model

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