Dual degradation image inpainting method via adaptive feature fusion and U-net network

U-Net: Convolutional Networks for Biomedical Image Segmentation

Ronneberger, O., Fischer, P., & Brox, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_28 · Cited by 99,404

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Zhang, R., Isola, P., Efros, A. A., Shechtman, E., & Wang, O. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00068 · Cited by 14,623

Deep High-Resolution Representation Learning for Visual Recognition

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Colorful Image Colorization

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FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising

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Learning Enriched Features for Real Image Restoration and Enhancement

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Progressive Image Deraining Networks: A Better and Simpler Baseline

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Residual Dense Network for Image Restoration

Zhang, Y., Tian, Y., Kong, Y., Zhong, B., & Fu, Y. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2968521 · Cited by 904

Let there be color!

Iizuka, S., Simo‐Serra, E., & Ishikawa, H. (2016) · ACM Transactions on Graphics · doi:10.1145/2897824.2925974 · Cited by 830

Proceedings of the 25th ACM international conference on Multimedia

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Real-time user-guided image colorization with learned deep priors

Zhang, R., Zhu, J.-Y., Isola, P., Geng, X., Lin, A. S., Yu, T., & Efros, A. A. (2017) · ACM Transactions on Graphics · doi:10.1145/3072959.3073703 · Cited by 613

Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations

Liu, H., Jiang, B., Song, Y., Huang, W., & Yang, C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58536-5_43 · Cited by 324

TextureGAN: Controlling Deep Image Synthesis with Texture Patches

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Bringing Old Photos Back to Life

Wan, Z., Zhang, B., Chen, D., Zhang, P., Chen, D., Liao, J., & Wen, F. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00282 · Cited by 252

Learning Diverse Image Colorization

Deshpande, A., Lu, J., Yeh, M.-C., Chong, M. J., & Forsyth, D. A. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.307 · Cited by 207

Image Inpainting With Local and Global Refinement

Quan, W., Zhang, R., Zhang, Y., Li, Z., Wang, J., & Dong-ming Yan, A. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3152624 · Cited by 204

Reference-Based Sketch Image Colorization Using Augmented-Self Reference and Dense Semantic Correspondence

Lee, J., Kim, E., Lee, Y., Kim, D., Chang, J., & Choo, J. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00584 · Cited by 185

User-Guided Deep Anime Line Art Colorization with Conditional Adversarial Networks

Ci, Y., Ma, X., Wang, Z., Li, H., & Luo, Z. (2018) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3240508.3240661 · Cited by 146

Bridging Global Context Interactions for High-Fidelity Image Completion

Zheng, C., Cham, T., Cai, J., & Phung, D. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01122 · Cited by 140

Towards Vivid and Diverse Image Colorization with Generative Color Prior

Wu, Y., Wang, X., Li, Y., Zhang, H., Zhao, X., & Shan, Y. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01411 · Cited by 129

Uni-paint: A Unified Framework for Multimodal Image Inpainting with Pretrained Diffusion Model

Yang, S., Chen, X., & Liao, J. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612200 · Cited by 81

Image inpainting algorithm based on inference attention module and two-stage network

Chen, Y., Xia, R., Yang, K., & Zou, K. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109181 · Cited by 72

ATM-DEN: Image Inpainting via attention transfer module and Decoder-Encoder network

Zhang, S., & Chen, Y. (2025) · Signal Processing Image Communication · doi:10.1016/j.image.2025.117268 · Cited by 54

A Superpixel-Based Variational Model for Image Colorization

Fang, F., Wang, T., Zeng, T., & Zhang, G. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2908363 · Cited by 54

Example‐Based Colourization Via Dense Encoding Pyramids

Xiao, C., Han, C., Zhang, Z., Qin, J., Wong, T., Han, G., & He, S. (2019) · Computer Graphics Forum · doi:10.1111/cgf.13659 · Cited by 52

Probabilistic Image Colorization

Royer, A., Kolesnikov, A., & Lampert, C. H. (2017) · British Machine Vision Conference (BMVC) · doi:10.5244/c.31.85 · Cited by 48

Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects

Kim, E., Lee, S., Park, J.-H., Choi, S., Seo, C., & Choo, J. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01440 · Cited by 38

Unbiased Multi-modality Guidance for Image Inpainting

Yu, Y., Du, D., Zhang, L., & Luo, T. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19787-1_38 · Cited by 24

Image inpainting based on CNN-Transformer framework via structure and texture restoration

Li, Z., Han, N., Wang, Y., Zhang, Y., Yan, J., Du, Y., & Geng, G. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2024.112671 · Cited by 21

Image inpainting using diffusion models to restore eaves tile patterns in Chinese heritage buildings

Zhong, X., Chen, W., Guo, Z., Zhang, J., & Luo, H. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.105997 · Cited by 18

Removing visual occlusion of construction scaffolds via a two-step method combining semantic segmentation and image inpainting

Ding, Y., Liu, M., Zhang, M. X., & Luo, X. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109983 · Cited by 13

Guided Colorization Using Mono-Color Image Pairs

Sheng, Z., Shen, H., Yao, B., & Zhang, H. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3235536 · Cited by 12

Context-aware mutual learning for blind image inpainting and beyond

Zhao, H., Wang, Y., Gu, Z., Zheng, B., & Zheng, H. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.126224 · Cited by 10

Image inpainting for periodic discrete density defects via frequency analysis and an adaptive transformer-GAN network

Ding, H., Huang, Y., Chen, N., Lu, J., & Li, S. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.112410 · Cited by 9

A novel image inpainting method based on a modified Lengyel–Epstein model

Wang, J., Luo, M., Chen, X., Xu, H., & Kim, J. (2024) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2024.104195 · Cited by 9

Image inpainting via Multi-scale Adaptive Priors

Wang, Y., Guo, D., Zhao, H., Yang, M., & Zheng, H. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111410 · Cited by 8

RF-Inpainter: Multimodal Image Inpainting Based on Vision and Radio Signals

Chen, C., Nishio, T., Bennis, M., & Park, J. (2022) · IEEE Access · doi:10.1109/access.2022.3214972 · Cited by 5

MaGIC: Multi-modality Guided Image CompletionPreprint

Yu, Y., Wang, H., Luo, T., Fan, H., & Zhang, L. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2305.11818 · Cited by 3

U2-LFOR: A Two-Stage U2 Network for Light-Field Occlusion Removal

Senussi, M. F., Abdalla, M. I., Kasem, M. S., Mahmoud, M., & Kang, H. (2025) · Mathematics · doi:10.3390/math13172748 · Cited by 18

SDN-Driven Multi-Objective Task Offloading in IoT-Enabled UAVs in Edge-Cloud Computing Using Double DQN

Ullah, A., Ullah, I., Haq, Q. M. U., Rubab, S., Baili, J., & Khan, M. A. (2025) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2025.3597723 · Cited by 12

Improved BOTSORT multi-object tracking algorithm for robotic rollers using feature-level fusion of millimeter-wave radar and camera sensors

Liang, H., Wang, J., Zhang, J., Wang, X., Guan, S., & Yu, H. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103294 · Cited by 12

PromptDNet: A weakly supervised prompt framework for single image dehazing via dual-level depth cues

Wang, J., Wang, S., Pang, Y., & Liu, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111997 · Cited by 9

Automated image inpainting for historical artifact restoration using hybridisation of transfer learning with deep generative models

Swathi, B., & Rao, D. B. J. (2026) · Scientific Reports · doi:10.1038/s41598-026-35056-w · Cited by 9

Dual image degradation repair network based on adaptive multifeature fusion

Zhao, X., Peng, C., & Zhang, X. (2023) · Scientia Sinica Technologica · doi:10.1360/sst-2022-0435 · Cited by 1

Deep Learning based Image Inpainting and Restoration System using Partial Convolutional Networks, Autoencoders, and U-Net Architectures

Anjaneyulu, Y., Swetha, P. M., Priyanka, V., Kumar, K. V., Sristi, J., & Neelima, G. (2025) · International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS) · doi:10.1109/icicnis66685.2025.11315749

Adaptive Dual Fusion Network for All-in-One Image Restoration

Gao, T., Cao, Y., Lyu, Y., Wen, Y., & Chen, T. (2025) · International Conference on Vision, Image and Signal Processing (ICVISP) · doi:10.1109/icvisp68610.2025.11451707

An Image Inpainting Method Based on Bidirectional Feature Enhancement and Multi-Scale Feature Aggregation

Zhou, Z., Zhang, D., Gong, R., Chen, J., & Alqahtani, F. H. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-1565-3_6

Learning to Restore Multi-Degraded Images via Ingredient Decoupling and Task-Aware Path AdaptationPreprint

Gao, H., Lei, X., Zhang, Y., Xu, X., Jiang, G., & Ma, L. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2511.04920