Rethinking Portrait Matting with Privacy Preserving

[1]  D. Tao,et al.  ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond , 2022, International Journal of Computer Vision.

[2]  Jing Zhang,et al.  Referring Image Matting , 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[3]  Brian L. Price,et al.  Boosting Robustness of Image Matting with Context Assembling and Strong Data Augmentation , 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[4]  Jia Deng,et al.  A Study of Face Obfuscation in ImageNet , 2021, ICML.

[5]  S. Maybank,et al.  Bridging Composite and Real: Towards End-to-End Deep Image Matting , 2020, International Journal of Computer Vision.

[6]  Jiake Xie,et al.  Tripartite Information Mining and Integration for Image Matting , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[7]  Dacheng Tao,et al.  Deep Automatic Natural Image Matting , 2021, IJCAI.

[8]  Dacheng Tao,et al.  ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias , 2021, NeurIPS.

[9]  Dacheng Tao,et al.  Privacy-Preserving Portrait Matting , 2021, ACM Multimedia.

[10]  Chi-Keung Tang,et al.  Semantic Image Matting , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Ira Kemelmacher-Shlizerman,et al.  Real-Time High-Resolution Background Matting , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Ning Xu,et al.  Mask Guided Matting via Progressive Refinement Network , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Wen Gao,et al.  Pre-Trained Image Processing Transformer , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  Dacheng Tao,et al.  Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things , 2020, IEEE Internet of Things Journal.

[15]  S. Gelly,et al.  An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale , 2020, ICLR.

[16]  D. Tao,et al.  Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms , 2020, UAI.

[17]  Mei Wang,et al.  Deep Face Recognition: A Survey , 2018, Neurocomputing.

[18]  Stephen Lin,et al.  Swin Transformer: Hierarchical Vision Transformer using Shifted Windows , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

[19]  Rynson W. H. Lau,et al.  Is a Green Screen Really Necessary for Real-Time Portrait Matting? , 2020, ArXiv.

[20]  Dacheng Tao,et al.  Self-Supervised Pose Adaptation for Cross-Domain Image Animation , 2020, IEEE Transactions on Artificial Intelligence.

[21]  Jonathan Ullman,et al.  Auditing Differentially Private Machine Learning: How Private is Private SGD? , 2020, NeurIPS.

[22]  Yu Qiao,et al.  Attention-Guided Hierarchical Structure Aggregation for Image Matting , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Zhuo Chen,et al.  PuppeteerGAN: Arbitrary Portrait Animation With Semantic-Aware Appearance Transformation , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Miaomiao Cui,et al.  Boosting Semantic Human Matting With Coarse Annotations , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Ira Kemelmacher-Shlizerman,et al.  Background Matting: The World Is Your Green Screen , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Marco Forte,et al.  F, B, Alpha Matting , 2020, ArXiv.

[27]  Hongtao Lu,et al.  Natural Image Matting via Guided Contextual Attention , 2020, AAAI.

[28]  Lingyun Wu,et al.  MaskGAN: Towards Diverse and Interactive Facial Image Manipulation , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[29]  Kevin Duh,et al.  Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System? , 2019, TACL.

[30]  Qiang Xu,et al.  nuScenes: A Multimodal Dataset for Autonomous Driving , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[31]  Feng Liu,et al.  Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[32]  Hao Lu,et al.  Indices Matter: Learning to Index for Deep Image Matting , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[33]  Hujun Bao,et al.  A Late Fusion CNN for Digital Matting , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[34]  Dariu Gavrila,et al.  Privacy Protection in Street-View Panoramas Using Depth and Multi-View Imagery , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[35]  Dong Liu,et al.  Deep High-Resolution Representation Learning for Human Pose Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[36]  Rui Zhang,et al.  A Hybrid Approach to Privacy-Preserving Federated Learning , 2018, Informatik Spektrum.

[37]  Úlfar Erlingsson,et al.  The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks , 2018, USENIX Security Symposium.

[38]  Quan Chen,et al.  Semantic Human Matting , 2018, ACM Multimedia.

[39]  Tae-Hyun Oh,et al.  Semantic soft segmentation , 2018, ACM Trans. Graph..

[40]  Aljoscha Smolic,et al.  AlphaGAN: Generative adversarial networks for natural image matting , 2018, BMVC.

[41]  Mark Sandler,et al.  MobileNetV2: Inverted Residuals and Linear Bottlenecks , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[42]  Marc Pollefeys,et al.  Designing Effective Inter-Pixel Information Flow for Natural Image Matting , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[43]  Yoichi Sato,et al.  Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[44]  Ning Xu,et al.  Deep Image Matting , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  Xiaogang Wang,et al.  Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[46]  Zhuowen Tu,et al.  Aggregated Residual Transformations for Deep Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[47]  Vitaly Shmatikov,et al.  Membership Inference Attacks Against Machine Learning Models , 2016, 2017 IEEE Symposium on Security and Privacy (SP).

[48]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[49]  Jiaya Jia,et al.  Deep Automatic Portrait Matting , 2016, ECCV.

[50]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[51]  Somesh Jha,et al.  Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures , 2015, CCS.

[52]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[53]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[54]  Deepu Rajan,et al.  Improving Image Matting Using Comprehensive Sampling Sets , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[55]  Chi-Keung Tang,et al.  KNN Matting , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[56]  Jian Sun,et al.  A global sampling method for alpha matting , 2011, CVPR 2011.

[57]  Manuel Menezes de Oliveira Neto,et al.  Shared Sampling for Real‐Time Alpha Matting , 2010, Comput. Graph. Forum.

[58]  Yuanjie Zheng,et al.  Learning based digital matting , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[59]  Marco Zennaro,et al.  Large-scale privacy protection in Google Street View , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[60]  Stefan Katzenbeisser,et al.  Privacy-Preserving Face Recognition , 2009, Privacy Enhancing Technologies.

[61]  C. Rother,et al.  A perceptually motivated online benchmark for image matting , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[62]  Dima Damen,et al.  Recognizing linked events: Searching the space of feasible explanations , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[63]  Michael F. Cohen,et al.  Optimized Color Sampling for Robust Matting , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[64]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.