Pose-Guided Human Image Synthesis Based on Fusion Feature Feedback Mechanism

Youwen Huang; Peng Zhao; Yadong You

doi:10.3788/LOP57.141011

[1] Davidson T R, Falorsi L, Cao N D et al. -09-26)[2019-10-15]. https:∥arxiv., org/abs/1804, 00891(2018).

[2] Goodfellow I J, Pouget-Abadie J, Mirza M et al. Generative adversarial nets[C]∥Proceedings of the 27th International Conference on Neural Information Processing Systems, December 8-13, 2014, Montreal, Quebec, Canada., 2672-2680(2014).

[3] Pumarola A, Agudo A, Sanfeliu A et al. Unsupervised person image synthesis in arbitrary poses. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 8620-8628(2018).

[4] Huang H, Li Z, He R et al. -10-27)[2019-10-15]. https:∥arxiv., org/abs/1807, 06358(2018).

[5] Wiles O, Koepke A S, Zisserman A. X2Face: a network for controlling face generation using images, audio, and pose codes[M]. ∥Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science. Cham: Springer, 11217, 690-706(2018).

[6] Isola P, Zhu J Y, Zhou T H et al. Image-to-image translation with conditional adversarial networks. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 5967-5976(2017).

[7] Zhu J Y, Park T, Isola P et al. Unpaired image-to-image translation using cycle-consistent adversarial networks. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2242-2251(2017).

[8] Karras T, Laine S. -03-29)[2019-10-15][EB/OL]. Aila T. A style-based generator architecture for generative adversarial networks., org/abs/1812, 04948(2019). https://arxiv.

[9] Zhang S F, Liu M Y, Han Z X et al. Generation method of high dynamic range image from a single low dynamic range image based on retinex enhancement[J]. Journal of Computer-Aided Design & Computer Graphics, 30, 1015-1022(2018).

[10] Ma L Q, Jia X, Sun Q R et al. -01-28)[2019-10-15]. https:∥arxiv., org/abs/1705, 09368(2018).

[11] Bao J M, Chen D, Wen F et al. CVAE-GAN: fine-grained image generation through asymmetric training. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2764-2773(2017).

[12] Yu Y, Gong Z Q, Zhong P et al. Unsupervised representation learning with deep convolutional neural network for remote sensing images[M]. ∥Zhao Y, Kong X, Taubman D. Image and graphics. Lecture notes in computer science. Cham: Springer, 10667, 97-108(2017).

[13] Kiasari M A, Moirangthem D S, Lee M. Coupled generative adversarial stacked auto-encoder: CoGASA[J]. Neural Networks, 100, 1-9(2018).

[14] Liang L Y, Zhang T T, He W. Head pose estimation based on multi-scale convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 131003(2019).

[15] Cao Z, Simon T, Wei S et al. Realtime multi-person 2D pose estimation using part affinity fields. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 1302-1310(2017).

[16] Deng J, Dong W, Socher R et al. ImageNet: a large-scale hierarchical image database. [C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL, USA. New York: IEEE, 248-255(2009).

[17] Zhang H, Sang Q B. No reference video quality assessment based on transfer learning[J]. Laser & Optoelectronics Progress, 55, 091101(2018).

[18] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Proceedings of the 25th International Conference on Neural Information Processing Systems, December 3-6, 2012, Lake Tahoe, Nevada, United States. New York: Curran Associates Inc, 1097-1105(2012).

[19] Mathieu M, Couprie C. -02-26)[2019-10-15]. https:∥arxiv., org/abs/1511, 05440(2016).

[20] Liu Z W, Luo P, Qiu S et al. DeepFashion: powering robust clothes recognition and retrieval with rich annotations. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1096-1104(2016).

[21] Zheng L, Shen L Y, Tian L et al. Scalable person re-identification: a benchmark. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 1116-1124(2015).

[22] Yao J C, Liu G Z. Improved SSIM IQA of contrast distortion based on the contrast sensitivity characteristics of HVS[J]. Iet Image Processing, 12, 872-879(2018).

[23] Salimans T, Goodfellow I J, Zaremba W et al. -06-10)[2019-10-15]. https:∥arxiv., org/abs/1606, 03498(2016).

[24] Shi W Z, Caballero J, Huszár F et al. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. [C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 1874-1883(2016).

[25] Johnson J, Alahi A, Li F F. Perceptual losses for real-time style transfer and super-resolution[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9906, 694-711(2016).

[26] Ma L Q, Sun Q R, Georgoulis S et al. Disentangled person image generation. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 99-108(2018).

[27] Esser P, Sutter E. A variational U-Net for conditional appearance and shape generation. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 8857-8866(2018).

[28] Simonyan K. -04-10)[2019-10-15]. https:∥arxiv., org/abs/1409, 1556(2015).

[29] Wu J L, Huang H B, Liu L G. Texture details preserving seamless image composition[J]. Journal of Zhejiang University (Engineering Science), 47, 951-956(2013).

[30] Tang X L, Du Y M, Liu Y W et al. Image recognition with conditional deep convolutional generative adversarial networks[J]. Acta Automatica Sinica, 44, 855-864(2018).

[31] Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation[M]. ∥Navab N, Hornegger J, Wells W, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science. Cham: Springer, 9351, 234-241(2015).

[32] Ren X L, Wang Y P, Yang J Y et al. Building detection from remote sensing images based on improved U-Net[J]. Laser & Optoelectronics Progress, 56, 222801(2019).

[33] Zhang F, Wu Y, Xiao Z T et al. Nanoparticle segmentation based on U-Net convolutional neural network[J]. Laser & Optoelectronics Progress, 56, 061005(2019).