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

Wang, J., Sun, K., Cheng, T., Jiang, B., Deng, C., Zhao, Y., Liu, D., Mu, Y., Tan, M., Wang, X., et al. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2983686 · Cited by 4,894

Colorful Image Colorization

Zhang, R., Isola, P., & Efros, A. A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46487-9_40 · Cited by 3,417

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

Zhang, K., Zuo, W., & Zhang, L. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2839891 · Cited by 2,990

Learning Enriched Features for Real Image Restoration and Enhancement

Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M., & Shao, L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58595-2_30 · Cited by 1,107

Progressive Image Deraining Networks: A Better and Simpler Baseline

Ren, D., Zuo, W., Hu, Q., Zhu, P., & Meng, D. (2019) · 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.2019.00406 · Cited by 1,072

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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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

Optimized hyperparameters for retail sales forecasting using grid search

Vhatkar, M. S., Mahajan, P. S., Raut, R. D., Cheikhrouhou, N., & Ghoshal, S. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111472 · Cited by 8

PIAN: A physics-informed assimilation neural network for temporal super-resolution reconstruction of sensor data in satellite attitude control system

Wang, Y., Song, Y., & Liu, D. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103805 · Cited by 8

Mamba with multi-frequency perception for image super-resolution

Yang, H., Xiao, J., Zhang, J., Zhou, X., & Liu, Y. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114570 · Cited by 7

ResKANNet: A residual Kolmogorov-Arnold network with multi-scale attention for brain tumor segmentation

Li, Z., Kang, Z., Wang, Y., Kang, X., Yang, S., & Zhao, Q. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132062 · Cited by 7

MSHF-YOLO: Cotton growth detection algorithm integrated multi-semantic and high-frequency features

Luo, J., Wu, Q., Wang, Y., Zhou, Z., Zhuo, Z., & Guo, H. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105423 · Cited by 5

Consistency-informed progressive learning and segment anything model for edge detection

Yang, W., Chen, Y., Qin, H., Chen, X.-D., & Tao, X. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113487 · Cited by 4

DBTSR: A U-shaped adaptive sparse transformer for single remote sensing image super-resolution

Tang, T., Liu, J., Luo, X., Gao, X., & Pan, X. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129424 · Cited by 4

Hierarchical text classification with enhanced graph encoding and dual-Natured text-label relationship

Kumar, A., & Toshniwal, D. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114676 · Cited by 4

St-diffnet: Diffusion-based inpainting of dunhuang murals with structural and textural guidance

Jia, R., Du, S., Dang, W., Zhang, H., Liu, J., & Lian, J. (2025) · Multimedia Systems · doi:10.1007/s00530-025-02056-1 · Cited by 4

Personalized text-to-image generation with Large Language and Vision Assistant enhanced training

Luan, J., Zhang, Z., Xing, W., & Zhao, L. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112116 · Cited by 3

Edge-guided interactive fusion of texture and geometric features for Dunhuang mural image inpainting

Tian, R., Wu, T., Feng, D., Xin, Z., & Wang, L. (2025) · Displays · doi:10.1016/j.displa.2025.103297 · Cited by 3

Saliency-guided contrastive pretraining and attention-enhanced decoding for semi-supervised diabetic retinopathy lesion segmentation

Abraham, S. E., Kovoor, B. C., & Nidhi, S. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132379 · Cited by 3

DCFANet: Merging dynamic context clustering mamba and context-to-focus attention for medical image segmentation

Kui, X.-Y., Hu, Z.-P., Ji, Z.-X., Jiang, S., Xiao, Q.-M., Zou, Z.-W., Li, Q.-S., Li, Y., Zou, B.-J., & Chen, L.-M. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133326 · Cited by 3

Pseudo-depth-based deep neural network model for object detection

Li, S.-Q., Feng, W., Liu, B., Tong, X., & Li, Q. (2026) · Scientific Reports · doi:10.1038/s41598-026-45310-w · Cited by 3

Can large language models understand depth in monocular images without prior vision knowledge?

Xia, Z., Wu, T., & Wu, B. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111680 · Cited by 7

Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification

Chatterjee, S., Yassin, H., Dubost, F., Nürnberger, A., & Speck, O. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133460 · Cited by 3

Scale invariable hybrid-attention Generative Adversarial Network for Single Image Super Resolution

Singla, K., Pandey, R., & Ghanekar, U. (2025) · Pattern Recognition Letters · doi:10.1016/j.patrec.2025.08.011 · Cited by 2

WEHD-DETR: A real-time defect detection algorithm for sewer pipelines based on improved RT-DETR

Wei, G., Yu, Z., & Li, D. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105585 · Cited by 2

Texture generation and adaptive fusion networks for image inpainting

Shi, W., Wu, Y., & Wen, Y. (2025) · Displays · doi:10.1016/j.displa.2025.103287 · Cited by 2

Bridging cross-modal sparsity via adaptive pillar propagation and hierarchical multi-granularity feature distillation for 3D object detection

Wan, R., Meng, W., Zhao, T., & Wei, L. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132195 · Cited by 2

Dual pathway attention over attention network with multi-scale supervision for colonoscopy polyp segmentation

Ullah, I., Alomar, K., Jamel, L., Althobaiti, M. M., Othman, K. M., & Noorwali, A. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132448 · Cited by 2

Universum graph-embedded kernel-based weighted extreme learning machine for handling class imbalance

Raghuwanshi, B. S. (2026) · Expert systems with applications · doi:10.1016/j.eswa.2026.131243 · Cited by 1

MUL-UNet: A lightweight multi-weather image restoration network with enhanced edge preservation

Li, R., Zhang, S., Huang, X., Nie, J., & Liu, M. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.114756 · Cited by 2

SATMtracker: Hyperspectral object tracking based on scale-adaptive tensorSSA feature and motion evaluator

Yu, D., Wang, J., Li, Z., Lou, H., & Rong, S. (2026) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2026.104774 · Cited by 2

Ultraflexible and stretchable multifunctional synaptic memristor by molecular layer deposition

Ma, Y.-J., Sun, S., Huang, Y., Zhang, S., Fu, L.-L., Wang, X.-X., Yang, Z., Wei, J., Wu, D., & Li, A. (2026) · Applied Physics Letters · doi:10.1063/5.0304145 · Cited by 2

Leveraging ISTA-inspired Transformer and multi-scale CNN for image compressive sensing

Xie, Z.-H., Fan, Z.-C., Tang, H., Liu, L.-J., & Jiang, H. (2026) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2026.104809 · Cited by 2

Momentum-based prototype-centered learning for dynamic facial expression recognition

Liang, Z., Xia, H., Tan, Y., & Song, S. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105491 · Cited by 1

ACA-Net: Adaptive cloud-aware network for remote sensing image thick cloud removal

Hou, B., Li, Y., Dang, X., Wang, J., Zhao, Q., Qu, H., Yang, Y., Chen, X., & Jiang, B. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129859 · Cited by 1

Technologies of internet of things adoption difficulties in enterprises based on an integrated decision-making technique

Ki̇ri̇şçi̇, M. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114708 · Cited by 1

TOMPEI-CMMD: An adaptive radiological feature analysis using unitary U-net for high-precision mammography segmentation

Kalpana, V. P., & Thilagamani, S. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131982 · Cited by 1

Robustness-driven multi-UAV intention recognition framework: Integration of video data completion and feature learning

Zhao, M., Song, H., Ma, W., Liang, M., Zhang, Y., Zhu, J., Zhang, Y., & Liu, X. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.114356 · Cited by 1

An extensive experimental comparison of machine and deep learning methods for credit and bank fraud detection

Yapp, E. K. Y., & Yeh, H. (2025) · Finance research letters · doi:10.1016/j.frl.2025.109190 · Cited by 7

An annotation assistant for monitoring the electrical grid using aerial images

Benlliure-Jimenez, C., Peñate-Sánchez, A., Lorenzo-Navarro, J., Castrillón-Santana, M., & Tejera, F. M. H. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115355 · Cited by 1

MSCNRNet: Non-dense residual network with multi-skip connection for image restoration

Chen, Y., Luo, H., Shi, M., Ma, X., Li, H., & Yao, Q. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.114742 · Cited by 1

Subspace-frequency regularization for hyperspectral image super-resolution

Fang, C., Li, Y., Zhu, J., Qiu, H., Xu, H., & Zheng, J. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115620 · Cited by 1

High-precision automated grading of flue-cured tobacco leaves based on hierarchical feature fusion

Pang, S.-P., Xin, X.-W., Ge, W., Zhang, Y., & Jia, J. (2026) · Scientific Reports · doi:10.1038/s41598-026-45252-3 · Cited by 2

Probabilistic similarity preservation for distribution discrepancy reduction in domain adaptation

Hatefi, E., Karshenas, H., & Adibi, P. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111426 · Cited by 1

Temporally consistent low-light face video enhancement via video-to-video conditional diffusion

Ding, X., He, K., Sun, H., & Yang, J. (2026) · Scientific Reports · doi:10.1038/s41598-026-44219-8

Utilizing time series analysis to forecast the growth of mobile payment users and its implications for the digital economy

Liang, T., & Li, S. L. (2025) · PLoS ONE · doi:10.1371/journal.pone.0327811

An effective two-dimensional code instance dollmaker masked convolutional network for QR code beautification

Rathi, J., & Grewal, S. K. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114329

A Novel High Gain DC‐DC Converter Based on Three‐Stage Voltage Multiplier Cell and Three‐Winding Coupled Inductor

Jin, T., Zheng, H., Chen, Y., Li, H., & Liu, Y. (2025) · International Journal of Circuit Theory and Applications · doi:10.1002/cta.70156

Forensic image classification with active learning and generative adversarial network-based data augmentation

Yu, X., Li, F., Wang, Q., Chen, W., & Fan, B. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105649

Light suppression enhancement network for complex night traffic image enhancement

Wang, X., Liu, M., Cao, Y., Gao, T., & Wang, D. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112605

Unraveling incomplete multiview data: An information-theoretic framework

Zhang, Q., Lu, M., Xin, J., & Chen, B. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.114405

Aggregated text steganalysis toward social network based on efficient multi-perspective feature fusion

Xu, Q., Zhang, R., Liu, J., & Huang, Y. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.115129

Hierarchical texture-aware image inpainting via contextual attention and multi-scale fusion

Li, R. G., Dai, J., Qin, Q., Wang, C., Yi, Y., & Wang, J. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105875

Reference-guided image inpainting via progressive feature interaction and reconstruction for mobile robots with binocular cameras

Liu, J., Li, H., Liu, H., Xie, S., & Luo, J. (2025) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2025.105320

CPFSSR: Combined permuted self-attention and fast Fourier transform-based network for stereo image super-resolution

Luo, W., Wu, J., Huang, F., & Li, Y. (2026) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105870

Image restoration method and optimization based on generative adversarial network model

Wu, Y. (2026) · Discover Applied Sciences · doi:10.1007/s42452-026-08237-5

Multivariate max-min sampling operators: Theory and applications in image processing

Vayeda, K., & Bajpeyi, S. (2026) · Applied Mathematics and Computation · doi:10.1016/j.amc.2026.129998

MATdiff: Mask-aware transformer with diffusion model for large-mask image inpainting

Wang, S.-X., Zhao, W.-J., Liang, J., Zhang, W.-M., & Zhao, S. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133042 · Cited by 2

Enhancing seismic inversion fidelity via adaptive multi-frequency and multi-scale fusion

Wang, Y.-M., Xu, Q., Pan, S.-L., Peng, B., & Min, F. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115562

Semi-supervised medical image lesion detection based on multi-head feature fusion

Xu, Z., Zhang, H., Yang, R., Liu, W., & Lukasiewicz, T. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115618

MPCSD-Net: A multi-scale physically constrained self-distillation method for super-resolution reconstruction

Sha, H., & Han, Z. (2026) · Computational Geosciences · doi:10.1016/j.cageo.2026.106158

MBP: Rethinking class-imbalanced semi-supervised learning from the multi-binary perspective

Ye, C.-T., Meng, Q., & Ouyang, J. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133273

A Method for Filling Blank Stripes in Electrical Imaging Based on the Fusion of Arbitrary Kernel Convolution and Generative Adversarial Networks

Ruhan, A., Liu, D., Cao, G., Meng, K., Zhao, T., Tian, L., Zhao, B., Lin, G., & Fang, S. (2026) · Applied Sciences · doi:10.3390/app16073267

AMETracker: transformer tracking with asymmetric mix encoder

Chen, W., Zhang, J., & Yu, L. (2026) · Signal, Image and Video Processing · doi:10.1007/s11760-026-05273-x

The fault diagnosis design based on concatenated neural network with self-attention mechanism and data preprocessing

Su, B.-W., Chen, X.-P., Dai, Y.-H., Guan, T., & Li, Y. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133757

Overcoming sparsity in micro ribonucleic acid-messenger ribonucleic acid regulatory networks: A graph sample and aggregate framework with learnable virtual nodes

Sun, Z.-P., Guo, L., Mu, J., Qu, T., & Pan, Y. (2026) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2026.114810

Quantile-based deep ensemble models for probabilistic forecasting of significant wave heights

Anand, P., Parate, P., & Mishra, R. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.115152

Transformer-based 3D pose estimation pipeline with modular SmoothNet integration for animation generation

Xu, X.-Y. (2026) · Scientific Reports · doi:10.1038/s41598-026-54621-x

Synthetic Image Detection Based on Multi-Level Feature Fusion and Data Augmentation

Lin, G.-H., Lin, Y.-T., & Chen, J.-L. (2026) · ICT Express · doi:10.1016/j.icte.2026.05.018

LSD-DETR: A lightweight sonar detection transformer of defect detection in underwater pipeline environmentsPreprint

Huang, Y., Han, Q., Su, N.-N., & Wang, J.-H. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6913250

Wavelet-enhanced Mamba with multi-domain feature learning for image inpainting

Wu, Z., Dai, J., Qin, Q., Gao, J., Zhang, H., & Yi, Y. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.133422

Dual-branch soft-activation switch distillation network for efficient image super-resolution

Tang, Y., Cai, X.-M., & Chen, J. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.115807

Named entity recognition based on fusion of global and local semantic features for Chinese electronic medical records

Luo, K., Yang, W., Chen, X., Wang, Y., Zhu, B., Yang, G., & He, L. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01658-6

A motion-based framework for real-time anomaly detection in crowded scenes

Mabrouk, D., Abdel-Fattah, M. A., & Taha, A. (2026) · Neural computing & applications (Print) · doi:10.1007/s00521-026-12260-3

Cascade network with detection and inpainting for low-quality phase images

Rongxin, L., Weixian, L., Sijin, 吴. W., & Renhao, L. (2026) · Optics Communications · doi:10.1016/j.optcom.2026.133541

SwinMED: Edge-texture enhanced SwinIR for medical image super-resolution

Aymaz, S., & Aymaz, Ş. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116665

BCMSI-Net: Bilinear channel and multi-directional spatial attention interaction network for dual-view diabetic retinopathy grading

Guo, Y.-F., Wang, Y.-C., Zhang, Z.-H., Ma, F., Meng, J., & Li, D.-P. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.111250

Cross-attention augmented U-Net for surrogate prediction of inter-electrode magnetic field distribution in vacuum circuit breaker

Yang, J., Liu, X., Chen, H., & Zou, J. (2026) · Electric Power Systems Research · doi:10.1016/j.epsr.2026.114082

Mamba-enhanced low-resolution prior guided Chinese painting image inpainting

Peng, X.-L., Hu, Q.-Y., Zhang, Z.-Y., Qu, S.-Y., Chen, N.-N., & Gabbouj, M. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.116397

Attribute-controlled diffusion model for diverse image inpainting

Han, N., Geng, G.-H., Deng, J.-H., & Li, Z. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.116396

A prediction and optimization framework for clamping stress of composite skin during fuselage assembly

Chen, Y., Wan, J., Kang, Y., Wang, H., Zhang, Y., & Bi, Y. (2026) · Aerospace Science and Technology · doi:10.1016/j.ast.2026.113805

LSD-DETR: A Lightweight Transformer-Based Detector for Sewer-Pipeline Defects in Forward-Looking Sonar Images

Huang, Y., 韩庆邦, Wang, J., Ge, K., Su, N., & Xia, J. (2026) · Sensors · doi:10.3390/s26185848

R-DAF: Towards discrete activation functions for improving the robustness of deep neural networks against adversarial attacks

Zandi, G., & Ashouri-Talouki, M. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.135135

An improved Gated Recurrent Unit model with hybrid network architecture for carbon emission forecasting in Zhejiang Province

Luo, X.-T., Wang, Y., & Ren, Y. (2026) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2026.116138

FoTa-Net: Boundary-conditioned spatial–spectral coordination for large mask image inpainting

Peng, H., Wang, K.-H., Zheng, W.-F., Lan, G.-S., & Yu, Y. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.116520

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