What's in a Decade? Transforming Faces Through Time

被引:3
作者
Chen, Eric Ming [1 ]
Sun, Jin [2 ]
Khandelwal, Apoorv [3 ]
Lischinski, Dani [4 ]
Snavely, Noah [1 ]
Averbuch-Elor, Hadar [5 ]
机构
[1] Cornell Univ, Ithaca, NY 14853 USA
[2] Univ Georgia, Athens, GA 30602 USA
[3] Brown Univ, Providence, RI 02912 USA
[4] Hebrew Univ Jerusalem, Jerusalem, Israel
[5] Tel Aviv Univ, Tel Aviv, Israel
基金
美国国家科学基金会;
关键词
CCS Concepts; Computer graphics; Computer vision; Computing methodologies → Image manipulation;
D O I
10.1111/cgf.14761
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
How can one visually characterize photographs of people over time? In this work, we describe the Faces Through Time dataset, which contains over a thousand portrait images per decade from the 1880s to the present day. Using our new dataset, we devise a framework for resynthesizing portrait images across time, imagining how a portrait taken during a particular decade might have looked like had it been taken in other decades. Our framework optimizes a family of per-decade generators that reveal subtle changes that differentiate decades-such as different hairstyles or makeup-while maintaining the identity of the input portrait. Experiments show that our method can more effectively resynthesizing portraits across time compared to state-of-theart image-to-image translation methods, as well as attribute-based and language-guided portrait editing models. Our code and data will be available at facesthroughtime.github.io.
引用
收藏
页码:281 / 291
页数:11
相关论文
共 67 条
[1]   StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows [J].
Abdal, Rameen ;
Zhu, Peihao ;
Mitra, Niloy J. ;
Wonka, Peter .
ACM TRANSACTIONS ON GRAPHICS, 2021, 40 (03)
[2]   Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? [J].
Abdal, Rameen ;
Qin, Yipeng ;
Wonka, Peter .
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019), 2019, :4431-4440
[3]   Only a Matter of Style: Age Transformation Using a Style-Based Regression Model [J].
Alaluf, Yuval ;
Patashnik, Or ;
Cohen-Or, Daniel .
ACM TRANSACTIONS ON GRAPHICS, 2021, 40 (04)
[4]  
[Anonymous], 2014, EUR C COMP VIS
[5]  
Antic Jason., 2019, A deep learning based project for colorizing and restoring old images (and video!)
[6]   A morphable model for the synthesis of 3D faces [J].
Blanz, V ;
Vetter, T .
SIGGRAPH 99 CONFERENCE PROCEEDINGS, 1999, :187-194
[7]   Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation [J].
Chen, Liang-Chieh ;
Zhu, Yukun ;
Papandreou, George ;
Schroff, Florian ;
Adam, Hartwig .
COMPUTER VISION - ECCV 2018, PT VII, 2018, 11211 :833-851
[8]   StarGAN v2: Diverse Image Synthesis for Multiple Domains [J].
Choi, Yunjey ;
Uh, Youngjung ;
Yoo, Jaejun ;
Ha, Jung-Woo .
2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2020), 2020, :8185-8194
[9]  
Collins Edo., 2020, IEEE C COMPUT VIS PA
[10]  
Cui Claire Yuqing, 2021, Proceedings of the IEEE/CVF International Conference on Computer Vision, P1374