Tổng hợp biểu cảm khuôn mặt dựa trên các khuôn mặt tương tự

Abboud B, Davoine F, Dang M (2004) Facial expression recognition and synthesis based on an appearance model. Signal Process Image Commun 19(8):723–740. https://doi.org/10.1016/j.image.2004.05.009

Agarwal S, Chatterjee M, mukherjee DP (2012) Synthesis of emotional expressions specific to facial structure. In: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 12(28):1–28:8. ACM, New York, NY, USA. https://doi.org/10.1145/2425333.2425361

Aifanti N, Papachristou C, Delopoulos A (2010) The mug facial expression database. In: 11th International Workshop on Image Analysis for Multimedia Interactive Services WIAMIS 10:1–4

Averbuch-Elor H, Cohen-Or D, Kopf J, Cohen MF (2017) Bringing portraits to life. ACM Trans Graph 36(6):196:1–196:13. https://doi.org/10.1145/3130800.3130818

Bailey DG (2011) Design for embedded image processing on FPGAs. John Wiley & Sons

Bradski G (2000) The opencv library. Dr. Dobb’s J Softw Tools

Cheng Y, Ling S (2008) 3d animated facial expression and autism in Taiwan. In: Advanced Learning Technologies, 2008. ICALT’08. Eighth IEEE International Conference on, pp. 17–19. IEEE

Choi Y, Choi M, Kim M, Ha JW, Kim S, Choo J (2018) Stargan: Unified generative adversarial networks for multi-domain image-to-image translation. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 8789–8797. https://doi.org/10.1109/CVPR.2018.00916

Deb D, Zhang J, Jain AK (2020) Advfaces: Adversarial face synthesis. In: 2020 IEEE International Joint Conference on Biometrics (IJCB), pp. 1–10. https://doi.org/10.1109/IJCB48548.2020.9304898

Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) Imagenet: A large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248–255

Ding H, Sricharan K, Chellappa R (2018) Exprgan: Facial expression editing with controllable expression intensity. In: Thirty-Second AAAI Conference on Artificial Intelligence

Ekman P, Friesen WV, Ellsworth P (1972) Emotion in the human face: Guidelines for research and an integration of findings. Pergamon Press, Oxford, England

Ekman P, Friesen WV, Hager JC (2002) Facs investigator’s guide. A Hum Face

Everingham M, Eslami SM, Gool L, Williams CK, Winn J, Zisserman A (2015) The pascal visual object classes challenge: A retrospective. Int J Comput Vis 111(1):98–136. https://doi.org/10.1007/s11263-014-0733-5

Fujishiro H, Suzuki T, Nakano S, Mejima A, Morishima S (2009) A natural smile synthesis from an artificial smile. In: SIGGRAPH ’09: Posters, SIGGRAPH ’09, pp. 59:1–59:1. ACM, New York, NY, USA. https://doi.org/10.1145/1599301.1599360

Geng J, Shao T, Zheng Y, Weng Y, Zhou K (2018) Warp-guided gans for single-photo facial animation. ACM Trans Graph 37(6). https://doi.org/10.1145/3272127.3275043

Ghent J, McDonald J (2005) Photo-realistic facial expression synthesis. Image Vis Comput 23(12), 1041–1050. https://doi.org/10.1016/j.imavis.2005.06.011

Golan O, Baron-Cohen S (2006) Systemizing empathy: Teaching adults with asperger syndrome or high-functioning autism to recognize complex emotions using interactive multimedia. Dev Psychopathol 591–617. https://doi.org/10.1017/S0954579406060305

Grynszpan O, Martin JC, Nadel J (2008) Multimedia interfaces for users with high functioning autism: An empirical investigation. International J Hum Comput Stud 66(8):628–639

He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770–778. https://doi.org/10.1109/CVPR.2016.90

Horn RA, Johnson CR (2012) Matrix Analysis, 2nd edn. Cambridge University Press, USA

Izard CE (1971) The face of emotion. Appleton-Century-Crofts, East Norwalk, CT, US

Jian M, Cui C, Nie X, Zhang H, Nie L, Yin Y (2019) Multi-view face hallucination using svd and a mapping model. Inf Scie 488:181–189. https://doi.org/10.1016/j.ins.2019.03.026. https://www.sciencedirect.com/science/article/pii/S0020025519302245

Jian M, Lam K (2015) Simultaneous hallucination and recognition of low-resolution faces based on singular value decomposition. IEEE Transactions on Circuits and Systems for Video Technology 25(11):1761–1772. https://doi.org/10.1109/TCSVT.2015.2400772

Jian M, Lam KM (2014) Face-image retrieval based on singular values and potential-field representation. Signal Process 100:9–15. https://doi.org/10.1016/j.sigpro.2014.01.004. https://www.sciencedirect.com/science/article/pii/S0165168414000073

Jian M, Lam KM, Dong J (2014) Facial-feature detection and localization based on a hierarchical scheme. Inf Sci 262:1–14. https://doi.org/10.1016/j.ins.2013.12.001. https://www.sciencedirect.com/science/article/pii/S0020025513008451

Kazemi V, Sullivan J (2014) One millisecond face alignment with an ensemble of regression trees. In: Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR ’14, pp. 1867–1874. IEEE Computer Society, Washington, DC, USA. https://doi.org/10.1109/CVPR.2014.241

King DE (2016) Dlib face detection dataset. http://dlib.net/. Accessed 25 Mar 2020

King DE (2017) High quality face recognition with deep metric learning. http://blog.dlib.net/2017/02/high-quality-face-recognition-with-deep.html . [Online; Acessado em: 01 Oct 2018]

Koestinger M, Wohlhart P, Roth PM, Bischof H (2011) Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization. In: Proceedings First IEEE International Workshop on Benchmarking Facial Image Analysis Technologies

Lahiri U, Bekele E, Dohrmann E, Warren Z, Sarkar N (2013) Design of a virtual reality based adaptive response technology for children with autism. IEEE Trans Neural Syst Rehab Eng 21(1):55–64

Learned-Miller E, Huang GB, RoyChowdhury A, Li H, Hua G (2016) Labeled Faces in the Wild: A Survey, pp. 189–248. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-319-25958-1_8

Li K, Dai Q, Wang R, Liu Y, Xu F, Wang J (2014) A data-driven approach for facial expression retargeting in video. IEEE Trans Multimed 16(2):299–310. https://doi.org/10.1109/TMM.2013.2293064

Li K, Xu F, Wang J, Dai Q, Liu Y (2012) A data-driven approach for facial expression synthesis in video. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 57–64. https://doi.org/10.1109/CVPR.2012.6247658

Li X, Chang CC, Chang SK (2007) Face alive icon. J Vis Lang Comput 18(4):440–453. https://doi.org/10.1016/j.jvlc.2007.02.008

Li Z, Zhu C, Gold C (2004) Digital terrain modeling: principles and methodology. CRC Press

Liu Z, Shan Y, Zhang Z (2001) Expressive expression mapping with ratio images. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’01, pp. 271–276. ACM, New York, NY, USA. https://doi.org/10.1145/383259.383289

Marčetić D, Soldić M, Ribarić S (2017) Hybrid cascade model for face detection in the wild based on normalized pixel difference and a deep convolutional neural network. In: M. Felsberg, A. Heyden, N. Krüger (eds.) Computer Analysis of Images and Patterns, pp. 379–390. Springer International Publishing, Cham

Masi I, Wu Y, Hassner T, Natarajan P (2018) Deep face recognition: A survey. In: 2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 471–478. https://doi.org/10.1109/SIBGRAPI.2018.00067

Mena-Chalco J, Junior RC, Velho L (2008) Banco de dados de faces 3d: Impa-face3d. Tech Rep IMPA - RJ. http://app.visgraf.impa.br/database/faces/

Mendi E, Bayrak C (2011) Facial animation framework for web and mobile platforms. In: 2011 IEEE 13th International Conference on e-Health Networking, Appl Serv 52–55. https://doi.org/10.1109/HEALTH.2011.6026785

Mima D, Kubo H, Maejima A, Morishima S (2011) Automatic generation of facial wrinkles according to expression changes. In: SIGGRAPH Asia 2011 Posters, SA ’11, pp. 1:1–1:1. ACM, New York, NY, USA. https://doi.org/10.1145/2073304.2073306

Moghadam SM, Seyyedsalehi SA (2018) Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition. Neural Netw. https://doi.org/10.1016/j.neunet.2018.05.016

Ng H, Winkler S (2014) A data-driven approach to cleaning large face datasets. In: 2014 IEEE International Conference on Image Processing (ICIP), pp. 343–347. https://doi.org/10.1109/ICIP.2014.7025068

Noh JY, Neumann U (2001) Expression cloning. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ’01, pp. 277–288. ACM, New York, NY, USA. https://doi.org/10.1145/383259.383290

Otberdout N, Daoudi M, Kacem A, Ballihi L, Berretti S (2020) Dynamic facial expression generation on hilbert hypersphere with conditional wasserstein generative adversarial nets. IEEE Transactions on Pattern Analysis and Machine Intelligence pp. 1–1. https://doi.org/10.1109/TPAMI.2020.3002500

Parkhi OM, Vedaldi A, Zisserman A (2015) Deep face recognition. Br Mach Vis Conf

Pickering MJ, Rüger S (2003) Evaluation of key frame-based retrieval techniques for video. Comput Vis Image Underst 92(2–3):217–235. https://doi.org/10.1016/j.cviu.2003.06.002

Sagonas C, Antonakos E, Tzimiropoulos G, Zafeiriou S, Pantic M (2016) 300 faces in-the-wild challenge: database and results. Image and Vision Computing 47:3–18. https://doi.org/10.1016/j.imavis.2016.01.002. http://www.sciencedirect.com/science/article/pii/S0262885616000147. 300-W, the First Automatic Facial Landmark Detection in-the-Wild Challenge

Seo M, Chen YW (2012) Two-step subspace learning for texture synthesis of facial images. In: 2012 6th International Conference on New Trends in Information Science and Service Science and Data Mining (ISSDM), pp. 483–486

Song L, Lu Z, He R, Sun Z, Tan T (2018) Geometry guided adversarial facial expression synthesis. In: Proceedings of the 26th ACM International Conference on Multimedia, MM ’18, pp. 627–635. ACM, New York, NY, USA. https://doi.org/10.1145/3240508.3240612

Testa RL, Corra CG, Machado-Lima A, Nunes FLS (2019) Synthesis of facial expressions in photographs: Characteristics, approaches, and challenges. ACM Comput Surv 51(6):124:1–124:35. https://doi.org/10.1145/3292652

Testa RL, Machado-Lima A, Nunes FLS (2018) Factors influencing the perception of realism in synthetic facial expressions. In: 2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 297–304. https://doi.org/10.1109/SIBGRAPI.2018.00045

Thies J, Zollhöfer M, Nieundefinedner M (2019) Deferred neural rendering: Image synthesis using neural textures. ACM Trans Graph 38(4). https://doi.org/10.1145/3306346.3323035

Tulyakov S, Liu MY, Yang X, Kautz J (2018) Mocogan: Decomposing motion and content for video generation. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 1526–1535. https://doi.org/10.1109/CVPR.2018.00165

Udupa JK, LeBlanc VR, Zhuge Y, Imielinska C, Schmidt H, Currie LM, Hirsch BE, Woodburn J (2006) A framework for evaluating image segmentation algorithms. Comput Med Imaging Graph 30(2):75–87. https://doi.org/10.1016/j.compmedimag.2005.12.001

Vondrick C, Pirsiavash H, Torralba A (2016) Generating videos with scene dynamics. In: D. Lee, M. Sugiyama, U. Luxburg, I. Guyon, R. Garnett (eds.) Advn Neural Inf Process Syst 29

Wang N, Gao X, Tao D, Yang H, Li X (2017) Facial feature point detection: A comprehensive survey. Neurocomputing. https://doi.org/10.1016/j.neucom.2017.05.013

Wang Y, Bilinski P, Bremond F, Dantcheva A (2020) Imaginator: Conditional spatio-temporal gan for video generation. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1149–1158. https://doi.org/10.1109/WACV45572.2020.9093492

Wang Z, Bovik AC (2006) Modern image quality assessment. Synth Lect Image Video Multimed Process 2(1):1–156

Wei W, Tian C, Maybank SJ, Zhang Y (2016) Facial expression transfer method based on frequency analysis. Pattern Recognit 49:115–128. https://doi.org/10.1016/j.patcog.2015.08.004

Xie W, Shen L, Jiang J (2017) A novel transient wrinkle detection algorithm and its application for expression synthesis. IEEE Transactions on Multimedia 19(2), 279–292. https://doi.org/10.1109/TMM.2016.2614429

Xie W, Shen L, Yang M, Jiang J (2018) Facial expression synthesis with direction field preservation based mesh deformation and lighting fitting based wrinkle mapping. Multimed Tools Appl 77(6):7565–7593 . https://doi.org/10.1007/s11042-017-4661-6

Xiong L, Zheng N, Du S, Wu L (2009) Extended facial expression synthesis using statistical appearance model. In: 2009 4th IEEE Conference on Industrial Electronics and Applications, pp. 1582–1587. https://doi.org/10.1109/ICIEA.2009.5138461

Xiong L, Zheng N, Liu, J, Du S, Liu Y (2010) Eye synthesis using the eye curve model. Image Vis Comput 28(3):329–342. https://doi.org/10.1016/j.imavis.2009.06.001

Xiong Z, Wu D, Gu W, Zhang H, Li B, Wang W (2020) Deep discrete attention guided hashing for face image retrieval. In: Proceedings of the 2020 International Conference on Multimedia Retrieval, ICMR ’20, p. 136-144. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3372278.3390683

Yang S, Luo P, Loy CC, Tang X (2016) Wider face: A face detection benchmark. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Zhang, H, Patel VM, Riggan BS, Hu S (2017) Generative adversarial network-based synthesis of visible faces from polarimetrie thermal faces. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), pp. 100–107. https://doi.org/10.1109/BTAS.2017.8272687

Zhou Y, Shi BE (2017) Photorealistic facial expression synthesis by the conditional difference adversarial autoencoder. In: 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII), pp. 370–376. https://doi.org/10.1109/ACII.2017.8273626