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Progressive Prompt-Driven Low-Light Image Enhancement With Frequency Aware Learning

Sun, X., Cheng, D., Li, Y., Wang, N., Zhang, D., Gao, X., & Sun, J. (2025) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2025.3586101 · Cited by 2 · see citing works

Gradient-Guided Diffusion-Based Restoration of Extremely Compressed Backgrounds for Video Coding for Machines

Dao, L. T. H., Vien, A. G., Lee, J., Jeong, S., Yang, N., & Lee, C. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3598710 · Cited by 2 · see citing works

Frequency-conditional diffusion model for low-light image enhancement

Zhao, L., Wang, J., Fan, C., Zheng, Z., & Zhang, X. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131383 · Cited by 2 · see citing works

Low-light image enhancement via self-degradation-aware and semantic-perceptual guidance networks

Ahmad, O. S., Anjuman, S. A., Bakr, S. S., & Bartani, A. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114571 · Cited by 2 · see citing works

ReciprocalLA-LLIE: Low-light image enhancement with luminance-aware reciprocal diffusion process

Lin, Z., Chen, W. P., Xu, J., Zeng, D., & Chen, M. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131438 · Cited by 2 · see citing works

Rethinking progressive low-light image enhancement: A frequency-aware tripartite multi-scale network

Li, Y., Zhang, K., Zhou, X., Zhang, Z., & Hu, S. Y. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.108351 · Cited by 2 · see citing works

Vision model fine-tuning based on two-level prompts fusion

Mao, K., & Fang, H. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.115185 · Cited by 2 · see citing works

Maximum-Value retinex decomposition guided generative priors for joint deraining and low-light image enhancement

Sun, Y., Wang, J., & Yin, R. (2026) · Information Sciences · doi:10.1016/j.ins.2026.123136 · Cited by 2 · see citing works

TOVO: Tone-oriented vision optimization for efficient low-light image enhancement

Razafindratovolahy, A., Rao, Y., Tovolahy, J. C., Afanga, M., & Mutale, A. (2026) · Signal Processing · doi:10.1016/j.sigpro.2026.110540 · Cited by 2 · see citing works

A Visual-Linguistic Approach for Robust RGB-Thermal Tracking With Dynamic Template Adaptation

Wang, X., Zheng, H., Liao, H., Zhang, Q., Ma, L., & Jiang, J. (2026) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2026.3668565 · Cited by 2 · see citing works

Semi-supervised teaching graph contrastive network for node classification

Shen, C., Song, J., Sun, Q., Guo, Q., & Tsang, E. C. C. (2026) · Electronic Research Archive · doi:10.3934/era.2026074 · Cited by 2 · see citing works

Social graph diffusion and disentangled representations learning for multimodal recommendation

Zhang, Z., Zhang, H., Wang, B., & Zhu, J. (2026) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-026-00612-x · Cited by 2 · see citing works

When One-Shot Federated Learning Meets Diffusion Models at the Edge: Technological Advances and Applications

Chen, W., Deng, D., Xiang, C., Liu, Z., & Xiao, B. (2026) · Journal of Intelligent Computing and Networking · doi:10.64509/jicn.21.64 · Cited by 2 · see citing works

An efficient deep unfolding approach for snapshot compressed imaging of motion videos

Yin, J., Tao, C., Hu, B., Wang, Y., & Wang, Q. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113554 · Cited by 2 · see citing works

SSFA-Net: Sparse strip and dual-domain spatial-frequency attention for efficient image dehazing

Babar, A. H., Hossain, M. S., Hussain, M., Zou, L., Gu, N., & Huang, Z. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133671 · Cited by 2 · see citing works

A wavelet-fusion attention prior network for low-light image enhancement

Li, Y., Wang, R., Yan, H., Luo, H., & Yin, J. (2026) · Digital Signal Processing · doi:10.1016/j.dsp.2026.106132 · Cited by 2 · see citing works

VCR: Variance-Driven Channel Recalibration for Robust Low-Light Enhancement

Cheng, Z., Zhang, F., Yin, X., Yin, B., & Wang, H. (2026) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2026.3689584 · Cited by 2 · see citing works

A spatially guided dual-path network for hyperspectral and multispectral image fusion

Liu, R., Li, J., Wang, P., & Zhu, C. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116227 · Cited by 2 · see citing works

WaveCD: Physics-guided wavelet cold diffusion for low-light image denoising

Chen, Z., CHEN, Y., Qin, P., Zhao, P., Chai, R., & Zeng, J. (2026) · Signal Processing · doi:10.1016/j.sigpro.2026.110730 · Cited by 2 · see citing works

Multi-scale cascaded network with high-low frequency for low-light image enhancement

Wu, J., Ran, T., Xiao, W., Yuan, L., & Tao, Q. (2025) · Computers & Graphics · doi:10.1016/j.cag.2025.104380 · Cited by 2 · see citing works

ColorAssist: Perception-Based Recoloring for Color Vision Deficiency Compensation

Lin, L., Xie, S., Wang, Y., Chen, B., Xue, Y., Zhuang, X., & Zhao, T. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3602643 · Cited by 2 · see citing works

Illuminating the Shadows: Enhanced Low-Light Image via a Retinex-based Model with Color Equalization

Liu, Z. M., Fan, T., Zhang, W., Wang, W., Huang, J., Lan, R., & Lu, H. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.129039 · Cited by 2 · see citing works

Incorporating Fourier Transformation With Diffusion Models for Low-Light Image Enhancement

Ma, A., Jiang, H., Liang, B., & Han, S. (2025) · IEEE Signal Processing Letters · doi:10.1109/lsp.2025.3575570 · Cited by 1 · see citing works

Deep visualization prior based video dehazing: a hybrid approach for enhanced visibility

Khaliq, Y., Irtaza, A., & Shah, S. M. A. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04289-z · Cited by 1 · see citing works

MVDT: Multiview Distillation Transformer for View‐Invariant Sign Language Translation

Guan, Z., Hu, Y., Jiang, H., Sun, Y., & Yin, B. (2025) · IET Computer Vision · doi:10.1049/cvi2.70038 · Cited by 1 · see citing works

Dual-stream noise suppression low-light image enhancement network based on Retinex theory

Han, G., Zeng, B., Rui, Z., Hu, Y., & Yu, X. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04514-9 · Cited by 1 · see citing works

Adversarial multimodal user-generated contents generation for anti-user identity linkage

Gao, J., Wu, B., Zheng, K., & Wu, C. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114978 · Cited by 1 · see citing works

Noise-Resilient Low-Light Image Enhancement with CLIP Guidance and Pixel-Reordering Subsampling

Song, S. (2025) · Electronics · doi:10.3390/electronics14244839 · Cited by 1 · see citing works

DFD-Stereo: Dual-Domain Feature Decoupling for Stereo Matching

Zhu, Z., Sun, F., Sun, J., & Li, H. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3633461 · Cited by 1 · see citing works

CoDiFSR: Code Diffusion paradigm with prior knowledge distillation for face super-resolution

Gu, J., Su, N., Wang, Z., Chen, S., Yang, W., & Wang, G. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113745 · Cited by 1 · see citing works

Complementary encoder refinement and multilevel crossmodal interaction for multimodal sarcasm detection

Guo, H., Huang, S., Geng, Z., Chen, J., Liu, S., & Kong, C. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116541 · Cited by 1 · see citing works

LL-Refiner: Learning Adaptive Refinement for Ultra-High-Definition Low-Light Image Enhancement

Yi, X., Yan, Q., Zhang, Y., Li, Z., Zhang, H., Cai, Z., & Ma, J. (2026) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2026.125939 · Cited by 1 · see citing works

MARINE-Net: Physics-guided lightweight CNN-INR architecture for underwater image restoration and color enhancement

Sriram, S., Vijayaraj, N., Swamynathan, V. P., Choudhary, G., & Thangavel, M. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.114463 · Cited by 1 · see citing works

Physics-guided atmospheric restoration network for single image dehazing

Hou, J., Gendy, G., & He, G. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-04411-1 · Cited by 1 · see citing works

Codebook prior-guided hybrid attention dehazing network

Huang, L., Zheng, H., Pan, L., Su, Z., & Wu, Q. (2025) · Image and Vision Computing · doi:10.1016/j.imavis.2025.105700 · Cited by 1 · see citing works

S 3 learning: image enhancement using optimized very deep homomorphic filtering enabled image enhancer

Prakash, V. N. V. S., Basha, M. M., Faruk, S. K. U., Madhurima, V., & Gundala, S. (2025) · The Imaging Science Journal · doi:10.1080/13682199.2025.2550060 · Cited by 1 · see citing works

Defense against unauthorized distillation in image restoration via feature space perturbation

Hu, H., Zheng, Z., & Lyu, C. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131984 · Cited by 1 · see citing works

USER: User-Side modality representation enhancement for multimodal recommendation

Fan, Y., Shi, D., Aguilar, J., & Zurada, J. M. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114943 · Cited by 1 · see citing works

InfoBFR: Real-World Blind Face Restoration via Information Bottleneck

Gao, N., Li, J., Huang, H., Zeng, Z., & He, R. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3637231 · Cited by 1 · see citing works

SWSTformer: A stationary wavelet-spatial attention multi-scale transformer framework for single image deraining

Xu, F., Xiong, R., Diao, L., Yang, H., Tong, N., & Li, F. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-05010-w · Cited by 1 · see citing works

Prompt-guided selective frequency network for real-world scene text image super-Resolution

Yan, X., Shan, T., Qin, H., Akhtar, N., Liu, Y., Rahmani, H., & Mian, A. S. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2025.112974 · Cited by 1 · see citing works

MoLA: Molecular multimodal layerwise adaptive network for molecular property prediction

Li, J., Zhang, Z. H., Lei, Z., Cheng, J., Ma, L., Liu, C., & Gao, S. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.115563 · Cited by 1 · see citing works

LFR-CMT-3D: Lipschitz-regularized multi-modal fusion for robust object detection in open-pit mines

Zhang, H., Liu, Y., Fang, Y., Liu, P., Yang, J., & Zhang, X. (2026) · Measurement Science and Technology · doi:10.1088/1361-6501/ae58c7 · Cited by 1 · see citing works

GA-CLIP: Dual-branch CLIP for generalizable and anomaly-aware zero-shot anomaly detection

Guo, W., Wan, Y., Yuan, S., Chang, L., Wu, Y., & Dou, Z. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116078 · Cited by 1 · see citing works

BIG-TM: Bridging Individual Guidance with Trifusion MoPoE for Chinese memes understanding

Wang, T., Li, J., Xue, F., Su, D., Su, G., Wen, X., & Sha, Y. (2026) · Knowledge-Based Systems · doi:10.1016/j.knosys.2026.116137 · Cited by 1 · see citing works

PriP: A training-free low-light image enhancement framework via content and illumination synergistic guidance

Liu, Y., Dong, X., Jin, Z., & Sha, W. (2026) · Computers & Graphics · doi:10.1016/j.cag.2026.104676 · Cited by 1 · see citing works

P-PatchDiff: Progressive Patch Diffusion Models for Low-Light Image Enhancement

Guo, R., Zhong, H., Pagnucco, M., & Song, Y. (2026) · International Journal of Computer Vision · doi:10.1007/s11263-026-02995-w · Cited by 1 · see citing works

KANDiff: Low-light Image Enhancement Based on Diffusion Models

Ren, Y., Yue, M., He, Y., & Zhang, L. (2025) · The European Journal on Artificial Intelligence · doi:10.1177/30504554251342571 · Cited by 1 · see citing works

Part-Attention-Based Pseudo-Label Refinement Reciprocal Compact Loss for Unsupervised Cattle Face Recognition

Liu, P., & Zhao, J. (2025) · Electronics · doi:10.3390/electronics14122343 · Cited by 1 · see citing works

MoCHA-former: Moiré-Conditioned Hybrid Adaptive Transformer for Video Demoiréing

Sung, J., Roh, C., Eom, C., & Oh, J. (2026) · Neurocomputing · doi:10.1016/j.neucom.2025.132477

Perceiving degradation prompts in residual diffusion model for real image denoising

Liu, M., Long, X., Tang, Q., Yao, C., & Zhao, Y. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.114090

A blur-guided multi-attention network based on left-right consistency for gradual defocus deblurring in binocular images

Chen, Z., Tang, Z., Zhong, Y., Zhang, H., Dai, Z., & Xie, Y. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131853

DMCDiff: Dynamic manifold constraint guided diffusion models for semi-supervised low-light image enhancement

Wu, X., Yu, Y., Ben, X., & Chen, L. (2025) · Digital Signal Processing · doi:10.1016/j.dsp.2025.105663

NOFA++: Tuning-Free NeRF-Based One-Shot Facial Avatar Reconstruction

Yu, W., Feng, C., Yuan, L., & Tian, Y. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3628119

CDMM: conditional diffusion model with mamba for low-light underwater image enhancement

Zheng, J., Lu, J., Zhao, R., Fu, Y., Liu, J., Luo, Z., & Li, X. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07981-6

Denoising diffusion post-processing for low-light image enhancement

Panagiotou, S., & Bosman, A. S. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110799 · Cited by 60 · see citing works

Degrade for upgrade: Learning degradation representations for real-world low-light image enhancement

Xu, L., Hu, C., Zhu, W., Wu, F., Cai, Z., Ye, M., & Lu, X. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109622 · Cited by 13 · see citing works

LLDE: Enhancing Low-Light Images with Diffusion Model

Ooi, X. P., & Chan, C. S. (2023) · Proceedings - International Conference on Image Processing · doi:10.1109/icip49359.2023.10222446 · Cited by 19 · see citing works

Degrade Is Upgrade: Learning Degradation for Low-Light Image Enhancement

Jiang, K., Wang, Z., Wang, Z., Chen, C., Yi, P., Lü, T., & Lin, C. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i1.19992 · Cited by 65 · see citing works

Robust low-light image enhancement in the wild via data synthesis and generative diffusion prior

Wang, Z., Lin, Q., Liu, F., Zhang, W., & Zhou, W. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113336 · Cited by 5 · see citing works