Learning Representations for Automatic Colorization

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

ImageNet Large Scale Visual Recognition Challenge

Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834

Normalized cuts and image segmentation

Shi, J., & Malik, J. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.868688 · Cited by 15,935

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftPreprint

Ioffe, S. (2024) · arXiv (Cornell University) · doi:10.57702/o9raffed · Cited by 15,273

Untitled work

(2010) · Cited by 14,134

Context Encoders: Feature Learning by Inpainting

Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.278 · Cited by 5,691

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2014) · arXiv · doi:10.48550/arxiv.1412.7062 · Cited by 4,213

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

Holistically-Nested Edge Detection

Xie, S., & Tu, Z. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.164 · Cited by 3,401

Set Representation Learning with Generalized Sliced-Wasserstein EmbeddingsPreprint

Naderializadeh, N., Kolouri, S., Comer, J. F., Andrews, R. W., & Hoffmann, H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.03892 · Cited by 6

From shades to vibrance: a comprehensive review of modern image colorization techniques

Geenath, O., & Priyadarshana, Y. H. P. P. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1626641 · Cited by 5

A survey on design choices for self-supervised learning in computer vision

Wittscher, L. (2026) · Artificial Intelligence Review · doi:10.1007/s10462-026-11506-9 · Cited by 4

Image colorization using Scaled-YOLOv4 detector

Hesham, M., Khaled, H., & Faheem, H. M. (2021) · International journal of intelligent computing and information sciences/International Journal of Intelligent Computing and Information Sciences · doi:10.21608/ijicis.2021.92207.1118 · Cited by 4

An Enhanced Image Colorization using Modified Generative Adversarial Networks with Pix2Pix Method

KumarSingh, N., Laddha, N., & James, J. (2023) · International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI) · doi:10.1109/raeeucci57140.2023.10134343 · Cited by 4

Clustering-Guided Twin Contrastive Learning for Endomicroscopy Image Classification

Zhou, J., Dong, X., & Liu, Q. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3366223 · Cited by 4

Lightweight Deep Exemplar Colorization via Semantic Attention-Guided Laplacian Pyramid

Zou, C., Wan, S., Blanch, M. G., Murn, L., Mrak, M., Sock, J., Yang, F., & Herranz, L. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3398791 · Cited by 4

Shadow-aware image colorization

Duan, X., Cao, Y., Zhang, R., Wang, X., & Li, P. (2024) · The Visual Computer · doi:10.1007/s00371-024-03500-5 · Cited by 4

GMK Net: Generative data-guided multiple kernel network for multimodal finger recognition

Huang, Y., Ma, H., & Wang, M. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125953 · Cited by 4

Adversarial network for unsupervised infrared image colorization based on full-scale feature fusion and cosine contrastive learning

Liu, T., Cai, Y., Chen, G., Wei, H., Bai, J., Liu, Y., Sui, X., & Chen, Q. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130713 · Cited by 4

Reconstruction of Full-Pol SAR Data from Partialpol Data Using Deep Neural Networks

Song, Q., Xu, F., & Jin, Y. Q. (2018) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2018.8518094 · Cited by 4

Video Colorization Using CNNs and Keyframes Extraction: An Application in Saving Bandwidth

Singh, A., Chanani, A., & Karnick, H. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-4018-9_18 · Cited by 4

Gray-Scale Image Colorization Using Cycle-Consistent Generative Adversarial Networks with Residual Structure Enhancer

Johari, M. M., & Behroozi, H. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9054432 · Cited by 4

What drives disease flows between locations?

Zhong, S., & Bian, L. (2020) · Transactions in GIS · doi:10.1111/tgis.12675 · Cited by 4

Attentional Colorization Networks with Adaptive Group-Instance Normalization

Gao, Y., Ding, Y., Wang, F., & Liang, H. (2020) · Information · doi:10.3390/info11100479 · Cited by 4

Semantic-driven Colorization

Ho, M. M., Zhang, L., Raake, A., & Zhou, J. (2021) · Conference on Visual Media Production · doi:10.1145/3485441.3485645 · Cited by 4

Two-stage pyramidal convolutional neural networks for image colorization

Wei, Y.-J., Wei, T.-T., Kuo, T.-Y., & Su, P.-C. (2021) · APSIPA Transactions on Signal and Information Processing · doi:10.1017/atsip.2021.13 · Cited by 4

Colorful Image Colorization with Classification and Asymmetric Feature Fusion

Wang, Z., Yu, Y., Li, D., Wan, Y., & Li, M. (2022) · Sensors · doi:10.3390/s22208010 · Cited by 4

Spatially Consistent Transformer for Colorization in Monochrome-Color Dual-Lens System

Xuan, D., Liu, C., Hu, X., Xu, K., & Li, W. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3215910 · Cited by 4

MLS-GAN: Multi-Level Semantic Guided Image Colorization

Chai, X., Liu, X., Zhang, H., Wang, H., Song, L., & Cao, L. (2022) · Proceedings - International Conference on Image Processing · doi:10.1109/icip46576.2022.9897614 · Cited by 4

Unifying Visual Contrastive Learning for Object Recognition from a Graph Perspective

Tang, S., Zhu, F., Bai, L., Zhao, R., Wang, C., & Ouyang, W. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19809-0_37 · Cited by 4

Unsupervised Scene Sketch to Photo Synthesis

Wang, J., Jeon, S., Yu, S. X., Zhang, X., Arora, H., & Lou, Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25063-7_17 · Cited by 4

Unsupervised Visual Representation Learning via Multi-Dimensional Relationship Alignment

Cheng, H., Li, H., Qiu, H., Wu, Q., Zhang, X., Meng, F., & Ngan, K. N. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3246801 · Cited by 4

Influence of Color Spaces for Deep Learning Image Colorization

Bugeau, A., Giraud, R., & Raad, L. (2023) · Springer eBooks · doi:10.1007/978-3-030-98661-2_125 · Cited by 4

A Novel Similarity Based Unsupervised Technique for Training Convolutional Filters

Erkoç, T., & Eskil, M. T. (2023) · IEEE Access · doi:10.1109/access.2023.3277253 · Cited by 4

Attention-Based Grayscale Image Colorization

Sun, L., Ju, D., & Ke, S. (2023) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma57826.2023.10216250 · Cited by 4

Real-Time User-guided Adaptive Colorization with Vision Transformer

Lee, G., Shin, S., Na, T., & Woo, S. S. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00054 · Cited by 4

Into the Colorful World of Webtoons: Through the Lens of Neural Networks

Cinarel, C., & Zhang, B. (2017) · IAPR International Conference on Document Analysis and Recognition (ICDAR) · doi:10.1109/icdar.2017.289 · Cited by 4

ColourAIze

Matulic, F. (2018) · ACM International Conference on Interactive Surfaces and Spaces (ISS) · doi:10.1145/3279778.3279785 · Cited by 4

Generating Trimap for Image Matting Using Color Co-Fusion

Li, J., Yuan, G., & Fan, H. (2019) · IEEE Access · doi:10.1109/access.2019.2896084 · Cited by 4

Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters

Kesen, İ., Can, O. A., Erdem, E., Erdem, A., & Yüret, D. (2022) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw56347.2022.00507 · Cited by 5

Self-supervised Cross-stage Regional Contrastive Learning for Object Detection

Yan, J., Yang, L., Gao, Y., & Zheng, W. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00183 · Cited by 4

SPDGAN: a generative adversarial network based on SPD manifold learning for automatic image colorization

Mourchid, Y., Donias, M., Berthoumieu, Y., & Najim, M. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-08999-8 · Cited by 4

A Review of Using Deep Learning Technology in the Built Environment of Disaster Management Phases

SÜNBÜL, G., & Soyluk, A. (2024) · Mimarlık Bilimleri ve Uygulamaları Dergisi (MBUD) · doi:10.30785/mbud.1333736 · Cited by 4

Reconstruction Full-Pol SAR Data from Single-Pol SAR Image Using Deep Neural Network

Song, Q., Xu, F., & Jin, Y. (2018) · China International SAR Symposium (CISS) · doi:10.1109/sars.2018.8551986 · Cited by 4

Image colourisation using deep feature‐guided image retrieval

Chakraborty, S. (2019) · IET Image Processing · doi:10.1049/iet-ipr.2018.6169 · Cited by 4

Dual feature extractor generative adversarial network for colorization

Tian, H., Kong, G., & Wu, Y. J. (2020) · Journal of Electronic Imaging · doi:10.1117/1.jei.29.4.043001 · Cited by 4

Automatic Image Colorization Using Adversarial Training

Lal, S., Garg, V., & Verma, O. P. (2017) · International Conference on Signal Processing Systems (ICSPS) · doi:10.1145/3163080.3163104 · Cited by 4

Self-supervised visual feature learning with curriculumPreprint

Keshav, V., & Delattre, F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.05634 · Cited by 4

Image Generation from Freehand Scene SketchesPreprint

Gao, C., Liu, Q., Xu, Q., Liu, J., Wang, L., & Zou, C. (2020) · arXiv (Cornell University) · Cited by 4

Multimodal Image-to-Image Translation via Mutual Information Estimation and MaximizationPreprint

Zuo, Z., Zhao, L., Wang, Z., Chen, H., Li, A., Xu, Q., Wei, X., & Lu, D. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.03529 · Cited by 4

Unsupervised Domain Adaptation with Temporal-Consistent Self-Training for 3D Hand-Object Joint ReconstructionPreprint

Qi, M., Remelli, E., Salzmann, M., & Fua, P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.11260 · Cited by 4

Self-Supervised AI-Generated Image Detection: A Camera Metadata Perspective

Zhong, N., Zou, M., Xu, Y., Qian, Z., Zhang, X., Wu, B., & Ma, K. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2026.3654274 · Cited by 4

HiStyle: Reinventing historic portraits via 3D generative model

Chen, Z., Yang, R., Yan, Y., & Zhu Li, B. (2024) · Displays · doi:10.1016/j.displa.2024.102725 · Cited by 3

Spcolor: Semantic prior guided exemplar-based image colorization

Chen, S., Zhang, X., Wang, M., Li, X., Zhang, Y., & Zhang, Y. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.111109 · Cited by 3

Melanoma Classification using GAN based augmentation and Self-Supervised feature extraction

Lal, A., Tiwari, S., Patra, R., & Agrawal, S. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825005 · Cited by 3

TinySurveillance: An Extra Low-Power Event-Based Surveillance Method for UAVs

Farahdel, A., Khan, A. H., Keshmiri, H., & Wahid, K. A. (2025) · IEEE Access · doi:10.1109/access.2025.3576192 · Cited by 3

SqueezeGAN: Image to Image Translation With Minimum Parameters

Kelkar, S., Rastogi, C., Gupta, S., & Pillai, G. N. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489587 · Cited by 3

FlowChroma - A Deep Recurrent Neural Network for Video Colorization

Wijesinghe, T., Abeysinghe, C., Wijayakoon, C., Jayathilake, L., & Thayasivam, U. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-50347-5_2 · Cited by 3

Multi-view 3D shape style transformation

Liu, X., Huang, H., Wang, W., & Zhou, J. (2021) · The Visual Computer · doi:10.1007/s00371-020-02042-w · Cited by 3

A Deep Neural Approach Toward Staining and Tinting of Monochrome Images

Neogi, D., Das, N., & Deb, S. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-16-2164-2_3 · Cited by 3

CNN-Based Spectral Super-Resolution of Panchromatic Night-Time Light Imagery: City-Size-Associated Neighborhood Effects

Rybnikova, N. A., Mirkes, E. M., & Gorban, A. N. (2021) · Sensors · doi:10.3390/s21227662 · Cited by 3

Histogram-Guided Semantic-Aware Colorization

Zhang, J., Xiao, Y., Chen, G., Sun, Q., Xu, F., & Leung, C.-S. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9747119 · Cited by 3

Fake Colorized Image Detection Approaches: A Review

Salman, K. A., Shaker, K., & Al-Janabi, S. T. F. (2022) · International Journal of Image and Graphics · doi:10.1142/s021946782350050x · Cited by 3

Ensemble Image Colorization using Convolutional Neural Network

Urmeneta, K. D., & Romero, V. M. (2022) · Proceeding of the Electrical Engineering Computer Science and Informatics · doi:10.23919/eecsi56542.2022.9946551 · Cited by 3

Improving Optical Flow Inference for Video Colorization

Huang, R., Li, S., Dai, W., Li, C., Zou, J., & Xiong, H. (2022) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas48785.2022.9937932 · Cited by 3

An effective architecture for Image colorization using Adaptive GAN

Ravindhar, N. V., Akshaya, K., Ramadevi, P. N. L., & Reddy, M. Y. (2023) · International Conference on Computer Communication and Informatics (ICCCI) · doi:10.1109/iccci56745.2023.10128511 · Cited by 3

Deep Learning-Based Machine Color Emotion Generation

Nie, T., & Lv, X.-G. (2023) · International Journal of Mobile Computing and Multimedia Communications · doi:10.4018/ijmcmc.325349 · Cited by 3

Cross-Modality Person Re-Identification Algorithm Based on Two-Branch Network

Song, J., Yang, J., Zhang, C., & Xie, K. (2023) · Electronics · doi:10.3390/electronics12143193 · Cited by 3

Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data

Moreu, E., Arazo, E., McGuinness, K., & O'Connor, N. E. (2023) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn54540.2023.10191896 · Cited by 3

Forensic analysis and detection using polycolor model binary pattern for colorized images

Agarwal, S., & Jung, K. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16675-1 · Cited by 3

Multilevel contrast strategy for unpaired image-to-image translation

Han, M., Shao, M., Meng, L., Liu, Y., & Qiao, Y. (2023) · Journal of Electronic Imaging · doi:10.1117/1.jei.32.6.063030 · Cited by 3

Vein pattern visualisation for biometric identification with cGAN on a New Zealand dataset

Keivanmarz, A., & Sharifzadeh, H. (2024) · Forensic Science International · doi:10.1016/j.forsciint.2024.112050 · Cited by 3

Anomaly classification based on self-supervised learning and its application

Han, Y., Qi, Z., & Tian, Y. (2024) · Journal of Radiation Research and Applied Sciences · doi:10.1016/j.jrras.2024.100918 · Cited by 3

Video Colorization Based on Variational Autoencoder

Zhang, G., Hong, X., Liu, Y., Qian, Y. Y., & Cai, X. (2024) · Electronics · doi:10.3390/electronics13122412 · Cited by 3

iReWindColor: Vision Transformer with Residual Embedding and Window Encoder for Point-Interactive Image Colorization

Ogura, H., & Ikehara, M. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890353 · Cited by 3

How Artificial Intelligence impacts the programs broadcast by Globo TV: Case studies

Antelo, A., & Hoyle, E. (2019) · SET INTERNATIONAL JOURNAL OF BROADCAST ENGINEERING · doi:10.18580/setijbe.2019.3 · Cited by 3

Medical Image Enhancement For Lesion Detection Based On Class-Aware Attention And Deep Colorization

Guo, J., Chen, J., Lu, C., & Huang, H. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9434019 · Cited by 3

Learning Positional Priors for Pretraining 2D Pose Estimators

Zhang, K., Yao, P., Wu, R., Yang, C., Li, D., Du, M., Deng, K., Liu, R., & Zheng, T. (2021) · International Workshop on Human-centric Multimedia Analysis (HCMA) · doi:10.1145/3475723.3484252 · Cited by 3

Recognition-oriented facial depth estimation from a single image

Chen, H., Yan, Y., Qin, J., Zhao, T., & Guo, T. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03560-x · Cited by 3

Colorization method of high resolution anime sketch with Pix2PixHD

Cui, J., Zhong, S., Chai, J., Zhu, L., Liu, B., Lin, L., Li, J., & Fang, X. (2021) · Asian Conference on Artificial Intelligence Technology (ACAIT) · doi:10.1109/acait53529.2021.9731216 · Cited by 3

Clustering-Based Representation Learning through Output Translation and Its Application to Remote-Sensing Images

Li, Q., Li, B., Garibaldi, J. M., & Qiu, G. (2022) · Remote Sensing · doi:10.3390/rs14143361 · Cited by 3

Unsupervised Scale-Invariant Multispectral Shape Matching

Pazi, I., Ginzburg, D., & Raviv, D. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/vhmq4826 · Cited by 5

Zoom-GAN: learn to colorize multi-scale targets

Liu, Y., Guo, Z., Guo, H., & Xiao, H. (2023) · The Visual Computer · doi:10.1007/s00371-023-02941-8 · Cited by 3

Learning from algorithm-generated pseudo-annotations for detecting ants in videos

Zhang, Y., Imirzian, N., Kurze, C., Zheng, H., Hughes, D. P., & Chen, D. Z. (2023) · Scientific Reports · doi:10.1038/s41598-023-28734-6 · Cited by 3

Self-Supervised Multimodal Fusion Network for Knee Osteoarthritis Severity Grading

Wu, W., Hu, K., Yue, W., Li, W., Simić, M., Li, C., Xiang, W., & Wang, Z. (2023) · International Conference on Digital Image Computing: Techniques and Applications (DICTA) · doi:10.1109/dicta60407.2023.00017 · Cited by 3

Automatic colourization of grayscale images based on tensor decomposition

Koushkaki, H. R., Salehi, M. R., & Abiri, E. (2017) · Multimedia Tools and Applications · doi:10.1007/s11042-017-5419-x · Cited by 3

Image Processing and Color Spaces

Hirai, K. (2017) · The Journal of The Institute of Image Information and Television Engineers · doi:10.3169/itej.71.306 · Cited by 3

SRAGAN: Generating Colour Landscape Photograph from Sketch

Chen, S.-B., Wang, P., Luo, B., Ding, C. H. Q., & Zhang, J. (2019) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8851754 · Cited by 3

Metric-Based Regularization and Temporal Ensemble for Multi-Task Learning using Heterogeneous Unsupervised Tasks

Song, B. C., Kim, D. H., & Lee, S. H. (2019) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2019.00352 · Cited by 3

Image Coding with Neural Network-Based Colorization

Lopes, D., Ascenso, J., Brites, C., & Pereira, F. M. B. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9413816 · Cited by 3

A Sensorimotor Perspective on Contrastive Multiview Visual Representation Learning

Laflaquière, A. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2021.3086267 · Cited by 3

Learn to Optimize Panchromatic Imagery for Accurate Building Extraction

Wang, Y., Wu, G., Feng, C., & Shibasaki, R. (2021) · IEEE Access · doi:10.1109/access.2021.3076933 · Cited by 3

Automatic Colorization of images using Auto-encoders

Sood, N., Nandakumar, N., & Rajkumar, S. (2021) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin52536.2021.9566101 · Cited by 3

CDVAE: Co-embedding Deep Variational Auto Encoder for Conditional Variational GenerationPreprint

Lu, J., Deshpande, A., & Forsyth, D. A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.00132 · Cited by 3

From One-Trick Ponies to All-Rounders: On-Demand Learning for Image Restoration.Preprint

Gao, R., & Grauman, K. L. (2016) · arXiv (Cornell University) · Cited by 3

Structural Consistency and Controllability for Diverse ColorizationPreprint

Messaoud, S., Forsyth, D. A., & Schwing, A. G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.02129 · Cited by 3

Few Shot Learning With No LabelsPreprint

Bharti, A., Vineeth, N. B., & Jawahar, C. V. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.13751 · Cited by 4

Towards Photorealistic Colorization by ImaginationPreprint

Lei, C., Wu, Y., & Chen, Q. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.09195 · Cited by 3

Evolutionary Machine Learning Meets Self-Supervised Learning: A Comprehensive Survey

Vinhas, A., Correia, J., & Machado, P. (2026) · IEEE Access · doi:10.1109/access.2026.3717264 · Cited by 3

Multi Fed-GANs: A Federated Generative Framework for Privacy-Preserving Image Colorization

Zare, M., Shamsinejad, P., & Kohan, A. (2025) · doi:10.1109/ipria68579.2025.11263532 · Cited by 2

Sustainable Entrepreneurship

Azimi, L., Hemmati, M., & Akbari, M. (2026) · University of Tehran science and humanities series · doi:10.1007/978-3-032-04909-4_3 · Cited by 2

Contrastive multi-view representation learning for multi-camera plant phenotyping: A cotton field study

Petti, D. J., Li, C., & Liu, N. (2026) · Plant Phenomics · doi:10.1016/j.plaphe.2026.100193 · Cited by 2

Enhanced memory colour in peripheral vision: A possible compensation for chromatic loss

Metzger, A., Valsecchi, M., & Toscani, M. (2026) · Vision Research · doi:10.1016/j.visres.2026.108802 · Cited by 2

Extended StyleGAN Encoder for Image Restoration

Lin, K., & Cai, Q. (2022) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr56361.2022.9956222 · Cited by 2

Semantic-Aware Gated Fusion Network For Interactive Colorization

Zhang, J., Xiao, Y., Zhenga, Y., Wang, Z., & Leung, C.-S. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10094771 · Cited by 2

CEDR: Contrastive Embedding Distribution Refinement for 3D point cloud representation

Yang, F., Cao, Y., Xue, Q., Jin, S., Li, X., & Zhang, W. (2024) · Signal Processing Image Communication · doi:10.1016/j.image.2024.117129 · Cited by 2

Learning by Aligning 2D Skeleton Sequences and Multi-modality Fusion

Tran, Q.-H., Ahmed, M., Popattia, M., Ahmed, M. H., Konin, A., & Zia, M. Z. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72973-7_9 · Cited by 2

Gray Scale Image Colorization for Human Faces

Zaware, S. N., Pathak, D., Patil, V., Sangale, G., & Gupta, V. (2021) · International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C) · doi:10.1109/icdi3c53598.2021.00030 · Cited by 2

Semantic-Based Few-Shot Classification by Psychometric Learning

Yin, L., Menkovski, V., Pei, Y., & Pechenizkiy, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-01333-1_31 · Cited by 2

Image Colorization Using a Deep Transfer Learning

Kiani, L., Saeed, M., & Nezamabadi–pour, H. (2020) · Iranian Joint Congress on Fuzzy and Intelligent Systems · doi:10.1109/cfis49607.2020.9238737 · Cited by 9

Colorful Image Colorization

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