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

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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

Anomaly detection of power line insulator from aerial imagery with attribute self-supervised learning

Ge, B., Hou, C., Liu, Y., Wang, Z., & Wu, R. (2021) · International Journal of Remote Sensing · doi:10.1080/01431161.2021.1934592 · Cited by 16

Omni-GAN: On the Secrets of cGANs and Beyond

Zhou, P., Xie, L., Ni, B., Geng, C., & Tian, Q. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.01380 · Cited by 17

A secure model on Advanced Fake Image-Feature Network (AFIFN) based on deep learning for image forgery detection

Ananthi, M., Rajkumar, P. R., Sabitha, R., & Karthik, S. (2021) · Pattern Recognition Letters · doi:10.1016/j.patrec.2021.10.011 · Cited by 15

Towards unsupervised classification of macromolecular complexes in cryo electron tomography: Challenges and opportunities

Moebel, E., & Kervrann, C. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.107017 · Cited by 15

Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation Learning

Gwilliam, M., & Shrivastava, A. (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/cvpr52688.2022.00942 · Cited by 17

Image Translation Between High-Resolution Remote Sensing Optical and SAR Data Using Conditional GAN

Niu, X., Yang, D., Yang, K., Pan, H., & Dou, Y. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00764-5_23 · Cited by 15

Automatic Cartoon Colorization Based on Convolutional Neural Network

Varga, D., Szabó, C. A., & Szirányi, T. (2017) · International Workshop on Content-Based Multimedia Indexing (CBMI) · doi:10.1145/3095713.3095742 · Cited by 15

Bamboo: Building Mega-Scale Vision Dataset Continually with Human–Machine Synergy

Zhang, Y., Sun, Q., Zhou, Y., He, Z., Yin, Z., Wang, K., Sheng, L., Qiao, Y., Shao, J., & Liu, Z. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02450-2 · Cited by 19

Implicit and explicit attention mechanisms for zero-shot learning

Alamri, F., & Dutta, A. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.03.009 · Cited by 14

DARTH: Holistic Test-time Adaptation for Multiple Object Tracking

Segù, M., Schiele, B., & Yu, F. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00891 · Cited by 15

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-Supervised Learning

Lv, P., Li, P., Zhu, S., Zhang, S., Chen, K., Liang, R., Yue, C., Xiang, F., Cai, Y., Ma, H., et al. (2024) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2024.24374 · Cited by 18

Online Supervised Training of Spaceborne Vision during Proximity Operations using Adaptive Kalman Filtering

Park, T. H., & D’Amico, S. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610138 · Cited by 14

Automatic Controllable Colorization via Imagination

Cong, X., Wu, Y., Chen, Q., & Lei, C. (2024) · 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/cvpr52733.2024.00252 · Cited by 16

A Multi-Task Self-Supervised Learning Framework for Scopy Images

Li, Y., Chen, J., & Zheng, Y. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098527 · Cited by 14

Learning to Cluster Under Domain Shift

Menapace, W., Lathuilière, S., & Ricci, E. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58604-1_44 · Cited by 14

Interactive Deep Colorization and its Application for Image Compression

Xiao, Y., Wu, J., Zhang, J., Zhou, P., Zheng, Y., Leung, C.-S., & Kavan, L. (2020) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2020.3021510 · Cited by 14

Semantic‐aware automatic image colorization via unpaired cycle‐consistent self‐supervised network

Xiao, Y., Jiang, A., Liu, C., & Wang, M. (2021) · International Journal of Intelligent Systems · doi:10.1002/int.22667 · Cited by 14

UGSC‐GAN: User‐guided sketch colorization with deep convolution generative adversarial networks

Zhang, J., Zhu, S., Kunxiang, L., & Liu, X. (2021) · Computer Animation and Virtual Worlds · doi:10.1002/cav.2032 · Cited by 14

HealNet - Self-supervised Acute Wound Heal-Stage Classification

Carrión, H., Jafari, M., Yang, H., Isseroff, R. R., Rolandi, M., Gomez, M. M., & Norouzi, N. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-21014-3_46 · Cited by 14

Twin Deep Convolutional Neural Network for Example-Based Image Colorization

Varga, D., & Szirányi, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-64689-3_15 · Cited by 14

An edge-refined vectorized deep colorization model for grayscale-to-color images

Su, Z., Liang, X., Guo, J., Gao, C., & Luo, X. (2018) · Neurocomputing · doi:10.1016/j.neucom.2018.05.082 · Cited by 14

Improving Few-Shot Learning using Composite Rotation based Auxiliary Task

Mazumder, P., Singh, P. P., & Namboodiri, V. P. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00270 · Cited by 14

Fully automatic image colorization based on semantic segmentation technology

Xu, M. G., & Ding, Y. (2021) · PLoS ONE · doi:10.1371/journal.pone.0259953 · Cited by 14

Conditional Image Generation for Learning the Structure of Visual Objects.Preprint

Jakab, T., Gupta, A., Bilen, H., & Vedaldi, A. (2018) · arXiv (Cornell University) · Cited by 14

A Weakly Supervised Method With Colorization for Nuclei Segmentation Using Point Annotations

Xia, L., Qu, Z., An, J., & Gao, Z. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3265124 · Cited by 14

Image Colorization Using Color-Features and Adversarial Learning

Shafiq, H., & Lee, B. (2023) · IEEE Access · doi:10.1109/access.2023.3335225 · Cited by 13

From superpixels to foundational models: An overview of unsupervised and generalizable image segmentation

Rodrigues, C. N., Nunes, I. M., Pereira, M. B., Oliveira, H., & dos Santos, J. A. (2024) · Computers & Graphics · doi:10.1016/j.cag.2024.104014 · Cited by 15

ColorMNet: A Memory-Based Deep Spatial-Temporal Feature Propagation Network for Video Colorization

Yang, Y., Dong, J., Tang, J., & Pan, J. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73235-5_19 · Cited by 13

Recent Approaches for Image Colorization

Pierre, F., & Aujol, J. (2021) · Springer eBooks · doi:10.1007/978-3-030-03009-4_55-1 · Cited by 14

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-resolution

Zhang, J., Xu, C., Li, J., Han, Y., Wang, Y., Tai, Y. Y., & Liu, Y. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20236 · Cited by 13

Robust Medical Image Colorization with Spatial Mask-Guided Generative Adversarial Network

Zhang, Z., Li, Y., & Shin, B. (2022) · Bioengineering · doi:10.3390/bioengineering9120721 · Cited by 13

Grayscale Image Colorization Using an Adaptive Weighted Average Method

Cao, L., Jiao, L., Li, Z., Liu, T., & Zhong, Y. (2017) · Journal of Imaging Science and Technology · doi:10.2352/j.imagingsci.technol.2017.61.6.060502 · Cited by 13

Robust Image Colorization Using Self Attention Based Progressive Generative Adversarial Network

Sharma, M. K., Makwana, M., Upadhyay, A., Singh, A. P., Badhwar, A., Trivedi, A., Saini, A., & Chaudhury, S. (2019) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2019.00272 · Cited by 14

Image Colorization Using the Global Scene-Context Style and Pixel-Wise Semantic Segmentation

Nguyen-Quynh, T.-T., Kim, S.-H., & Do, N.-T. (2020) · IEEE Access · doi:10.1109/access.2020.3040737 · Cited by 13

Color-UNet++: A resolution for colorization of grayscale images using improved UNet++

Di, Y., Zhu, X., Jin, X., Dou, Q., Zhou, W., & Duan, Q. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-10830-2 · Cited by 13

Neural-Network-Based Cross-Channel Intra Prediction

Li, Y., Yi, Y., Liu, D., Li, L., Zhu Li, B., & Li, H. (2021) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3434250 · Cited by 13

Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation

Boserup, N., & Selvan, R. (2023) · Proceedings of the Northern Lights Deep Learning Workshop · doi:10.7557/18.6798 · Cited by 14

Improving Transferability of Representations via Augmentation-Aware Self-SupervisionPreprint

Lee, H., Lee, K., Lee, K., Lee, H., & Shin, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.09613 · Cited by 15

Few-Shot Segmentation for Prohibited Items Inspection With Patch-Based Self-Supervised Learning and Prototype Reverse Validation

Liu, K. R., Lyu, S., & Lu, Y. (2022) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2022.3176546 · Cited by 14

Nowhere to Disguise: Spot Camouflaged Objects via Saliency Attribute Transfer

Zhao, W., Xie, S., Zhao, F., He, Y., & Lu, H. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3277793 · Cited by 12

Seamless Nudity Censorship: an Image-to-Image Translation Approach based on Adversarial Training

Móre, M. D., Souza, D. M., Wehrmann, J., & Barros, R. C. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489407 · Cited by 12

Collaborative Image and Object Level Features for Image Colourisation

Pucci, R., Micheloni, C., & Martinel, N. (2021) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw53098.2021.00245 · Cited by 12

Image colorization using deep convolutional auto-encoder with multi-skip connections

Jin, X., Di, Y., Jiang, Q., Chu, X., Duan, Q., Yao, S., & Zhou, W. (2022) · Soft Computing · doi:10.1007/s00500-022-07483-0 · Cited by 12

Image Colorization Algorithm Based on Deep Learning

Wang, N., Chen, G., & Tian, Y. (2022) · Symmetry · doi:10.3390/sym14112295 · Cited by 12

Quality Feature Learning via Multi-Channel CNN and GRU for No-Reference Video Quality Assessment

Kwong, N.-W., Chan, Y., Tsang, S., & Lun, D. P.-K. (2023) · IEEE Access · doi:10.1109/access.2023.3259101 · Cited by 12

Few-Shot Object Detection With Self-Supervising and Cooperative Classifier

Qi, D., Hu, J., & Shen, J. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3204597 · Cited by 12

Advanced multi-GANs towards near to real image and video colorization

Jampour, M., Zare, M., & Javidi, M. (2022) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-022-04206-z · Cited by 12

H&E-like staining of OCT images of human skin via generative adversarial network

Tsai, S.-T., Liu, C.-H., Chan, C., Li, Y.-H., Huang, S.-L. L., & Chen, H. H. (2022) · Applied Physics Letters · doi:10.1063/5.0122965 · Cited by 12

Cross-domain self-supervised few-shot learning via multiple crops with teacher-student network

Wang, G., Wang, Y., Zhang, J., Wang, X., & Pan, Z. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.107892 · Cited by 12

Self-supervised image co-saliency detection

Liu, Y., Li, T., Wu, Y., Song, H., & Zhang, K. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108533 · Cited by 11

Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation

Kuo, C.-W., Ma, C., Hoffman, J., & Kira, Z. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00116 · Cited by 11

Exploring efficient and effective generative adversarial network for thermal infrared image colorization

Chen, Y., Zhan, W., Jiang, Y., Zhu, D., Xu, X., & Guo, R. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01079-3 · Cited by 11

Beyond Instance Discrimination: Relation-Aware Contrastive Self-Supervised Learning

Zhang, Y., Liu, C., Zhou, Y., Wang, W., Ye, Q., & Ji, X. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3324588 · Cited by 11

Skin Lesion Segmentation using Deep Hypercolumn Descriptors

Ramachandram, D., & Taylor, G. W. (2017) · Journal of Computational Vision and Imaging Systems · doi:10.15353/vsnl.v3i1.173 · Cited by 11

Multi-Task Self-Supervised Visual Representation Learning for Monocular Road Segmentation

Cho, J. H., Kim, Y., Jung, H., Oh, C., Youn, J., & Sohn, K. (2018) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme.2018.8486472 · Cited by 11

Semantic Image Inpainting Using Self-Learning Encoder-Decoder and Adversarial Loss

Salem, N. M., Mahdi, H. M. K., & Abbas, H. M. (2018) · International Conference on Computer Engineering & Systems (ICCES) · doi:10.1109/icces.2018.8639258 · Cited by 11

Multi-GANs and its application for Pseudo-Coloring

Zare, M., Lari, K. B., Jampour, M., & Shamsinejad, P. (2019) · doi:10.1109/pria.2019.8786027 · Cited by 12

Self-Supervised Object Localization with Joint Graph Partition

Su, Y., Lin, G., Hao, Y., Cao, Y.-W., Wang, W., & Wu, Q. (2022) · AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i2.20127 · Cited by 17

Cantonese porcelain classification and image synthesis by ensemble learning and generative adversarial network

Chen, S.-C., Cui, H., Du, M., Fu, T., Sun, X., Ji, Y., & Duh, H. B. (2019) · Frontiers of Information Technology & Electronic Engineering · doi:10.1631/fitee.1900399 · Cited by 11

Boosting Supervision with Self-Supervision for Few-shot LearningPreprint

Su, J.-C., Maji, S., & Hariharan, B. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07079 · Cited by 11

RegionCL: Can Simple Region Swapping Contribute to Contrastive Learning?Preprint

Xu, Y., Zhang, Q., Zhang, J., & Tao, D. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.12309 · Cited by 14

Bridging the Domain Gap for Flight-Ready Spaceborne Vision

Park, T. H., & D’Amico, S. (2025) · Journal of Spacecraft and Rockets · doi:10.2514/1.a36130 · Cited by 10

A Practical Monochrome Video Colorization Framework for Broadcast Program Production

Endo, R., Kawai, Y., & Mchizuki, T. (2020) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2020.3028343 · Cited by 10

Learning disentangled representation for self-supervised video object segmentation

Hou, W., Qin, Z., Xi, X., Lu, X., & Yin, Y. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.01.066 · Cited by 10

Global and local representation collaborative learning for few-shot learning

Zhou, J., & Cai, Q. (2022) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-022-02066-0 · Cited by 10

RegionCL: Exploring Contrastive Region Pairs for Self-supervised Representation Learning

Xu, Y., Zhang, Q., Zhang, J., & Tao, D. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19827-4_28 · Cited by 12

Disturbed Augmentation Invariance for Unsupervised Visual Representation Learning

Cheng, H., Li, H., Wu, Q., Qiu, H., Zhang, X., Meng, F., & Zhao, T. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3272741 · Cited by 10

Learning to Blend Photos

Hung, W.-C., Zhang, J., Shen, X., Lin, Z., Lee, J.-Y., & Yang, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01234-2_5 · Cited by 10

Using Neural Networks for Fake Colorized Image Detection

Li, Y., Zhang, Y., Lu, L., Jia, Y., & Liu, J. (2019) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-28752-8_11 · Cited by 10

Improving the Generalization of Colorized Image Detection with Enhanced Training of CNN

Quan, W., Wang, K., Dong-ming Yan, A., Pellerin, D., & Zhang, X. (2019) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2019.8868802 · Cited by 10

Robust Perceptual Night Vision in Thermal Colorization

Almasri, F., & Debeir, O. (2020) · International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) · doi:10.5220/0008979603480356 · Cited by 10

Single Image Deraining Using Time-Lapse Data

Cho, J., Kim, S., Min, D., & Sohn, K. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3000612 · Cited by 10

Improving CNN-based colorization of B&W photographs

Boutarfass, S., & Besserer, B. (2020) · IEEE International Conference on Image Processing, Applications and Systems (IPAS) · doi:10.1109/ipas50080.2020.9334930 · Cited by 10

Image translation between high-resolution optical and synthetic aperture radar (SAR) data

Niu, X., Yang, D., Yang, K., Pan, H., Dou, Y., & Xia, F. (2021) · International Journal of Remote Sensing · doi:10.1080/01431161.2020.1836426 · Cited by 10

Semi-automatic Manga Colorization Using Conditional Adversarial Networks

Golyadkin, M., & Makarov, I. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-72610-2_17 · Cited by 10

Coloring Panchromatic Nighttime Satellite Images: Comparing the Performance of Several Machine Learning Methods

Rybnikova, N., Portnov, B. A., Mirkes, E. M., Zinovyev, A., Brook, A., & Gorban, A. N. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3076011 · Cited by 10

A Learned Representation of Artist-Specific Colourisation

van Noord, N., & Postma, E. O. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.343 · Cited by 10

Learning to Generate Facial Depth Maps

Pini, S., Grazioli, F., Borghi, G., Vezzani, R., & Cucchiara, R. (2018) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2018.00078 · Cited by 10

Learning Deep Image Priors for Blind Image Denoising

Hou, X., Luo, H., Liu, J., Xu, B., Sun, K., Gong, Y., Liu, B., & Qiu, G. (2019) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2019.00224 · Cited by 10

A Novel Building Temperature Simulation Approach Driven by Expanding Semantic Segmentation Training Datasets with Synthetic Aerial Thermal Images

Hou, Y., Volk, R., & Soibelman, L. (2021) · Energies · doi:10.3390/en14020353 · Cited by 10

Colorization of Logo Sketch Based on Conditional Generative Adversarial Networks

Tian, N., Liu, Y., Wu, B., & Li, X. (2021) · Electronics · doi:10.3390/electronics10040497 · Cited by 10

Improving Anomaly Segmentation with Multi-Granularity Cross-Domain Alignment

Zhang, J., Wu, X. Y., Cheng, Z.-Q., He, Q., & Li, W. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3611849 · Cited by 9

Beyond masking: Demystifying token-based pre-training for vision transformers

Tian, Y., Xie, L., Fang, J., Jiao, J., & Tian, Q. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111386 · Cited by 9

Detecting Persuasive Atypicality by Modeling Contextual Compatibility

Guo, M., Hwa, R., & Kovashka, A. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00101 · Cited by 12

Color Transfer Algorithm between Images Based on a Two-Stage Convolutional Neural Network

Xu, M., & Ding, Y. (2022) · Sensors · doi:10.3390/s22207779 · Cited by 9

An Improved Encoder-Decoder CNN with Region-Based Filtering for Vibrant Colorization

Gain, M., Rahman, M. A., Debnath, R., Alnfiai, M. M., Sheikh, A., Masud, M., & Bairagi, A. K. (2023) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.034809 · Cited by 9

ATOM: Self-supervised human action recognition using atomic motion representation learning

Degardin, B., Lopes, V., & Proença, H. P. M. C. (2023) · Image and Vision Computing · doi:10.1016/j.imavis.2023.104750 · Cited by 9

Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation

Wu, H., Zhang, Y., Ma, C., Guo, W., Tang, R., Liu, X., & Coates, M. (2023) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde55515.2023.00090 · Cited by 9

Contrastive Continuity on Augmentation Stability Rehearsal for Continual Self-Supervised Learning

Cheng, H., Wen, H., Zhang, X., Qiu, H., Wang, L., & Li, H. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00525 · Cited by 9

Grayscale Image Colorization Method Based onU-Net Network

Hu, Z., Shkurat, O., & Kasner, M. (2024) · International Journal of Image Graphics and Signal Processing · doi:10.5815/ijigsp.2024.02.06 · Cited by 9

Image Colorization with Neural Networks

Richart, M., Visca, J., & Baliosián, J. (2017) · Workshop of Computer Vision (WVC) · doi:10.1109/wvc.2017.00017 · Cited by 9

Hybrid Scheme of Image’s Regional Colorization Using Mask R-CNN and Poisson Editing

Ye, W., Chen, H., Zhang, Z., Liu, Y., Weng, S., & Chang, C. (2019) · IEEE Access · doi:10.1109/access.2019.2936258 · Cited by 9

Color Recovery from Multi-Spectral NIR Images Using Gray Information

Fu, Q., Jung, C., & Su, C. (2019) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3338533.3368259 · Cited by 9

Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement

Li, Z., Liu, C., Yuille, A., Ni, B., Zhang, W., & Gao, W. (2021) · 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/cvpr46437.2021.00964 · Cited by 9

Long future frame prediction using optical flow‐informed deep neural networks for enhancement of robotic teleoperation in high latency environments

Moniruzzaman, M., Rassau, A., Chai, D., & Islam, S. M. S. (2022) · Journal of Field Robotics · doi:10.1002/rob.22135 · Cited by 10

Optimal LED Spectral Multiplexing for NIR2RGB Translation

Liu, L., Chen, Y., Yan, J., & Zheng, Y. (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/cvpr52688.2022.01232 · Cited by 9

S 4 : Self-supervised learning with sparse-dense sampling

Tian, Y., Zhang, W., Su, P., Xu, Y., Zhuang, P., Xie, X., & Zhao, W. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112040 · Cited by 9

Research on Image Colorization Algorithm Based on Residual Neural Network

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