forked from ZPdesu/Barbershop
-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
312 lines (287 loc) · 9.13 KB
/
index.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
<!doctype html><meta charset=utf-8>
<head>
<!-- Global site tag (gtag.js) - Google Analytics -->
<!-- <script async src="https://www.googletagmanager.com/gtag/js?id=UA-152598381-4"></script> -->
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-152598381-4');
</script>
<meta property="twitter:image" content="https://zpdesu.github.io/Barbershop/thumbs/tr_paper-1.jpg" />
<meta property="og:image" content="https://zpdesu.github.io/Barbershop/thumbs/tr_paper-1.jpg"/>
<meta property="og:type" content="website"/>
<meta property="og:url" content="https://zpdesu.github.io/Barbershop/" />
<meta property="og:title" content="Barbershop: GAN-based Image Compositing using Segmentation Masks" />
<meta property="og:description" content="Barbershop: GAN-based Image Compositing using Segmentation Masks" />
</head>
<title>Barbershop: GAN-based Image Compositing using Segmentation Masks</title>
<style>
body {
font-family: Roboto, "Roboto", sans-serif;
background: #F0F0F0;
color: #696969;
/* text-align: center; */
/* padding: 0px 40px 40px 40px; */
}
h1 {
display: block;
font-size: 2em;
margin-top: 0.67em;
margin-bottom: 0px;
margin-left: 0;
margin-right: 0;
font-weight: normal;
color: #000;
}
h2 {
display: block;
font-size: 1.5em;
margin-top: 0.67em;
margin-bottom: 0.67em;
margin-left: 0;
margin-right: 0;
font-weight: normal;
color: #000;
}
h3 {
display: block;
font-size: 1em;
margin-top: 0.67em;
margin-bottom: 0.67em;
margin-left: 0;
margin-right: 0;
font-weight: normal;
}
h4 {
display: block;
font-size: 1.1em;
margin-top: 0.0em;
margin-bottom: 0.67em;
margin-left: 0;
margin-right: 0;
font-weight: normal;
color: #000;
}
hr {
border-top: 1px solid black;
}
.first-letter {
font-weight: 350;
display: inline;
font-size: 1.75em;
margin-block-start: 1em;
margin-block-end: 1em;
margin-inline-start: 0px;
margin-inline-end: 0px;
}
.paper-thumbnail {
box-shadow: 1px 2px 5px 2px rgba(0, 0, 0, .15);
width: 230px;
}
.grid-container {
display: grid;
grid-template-columns: auto auto auto auto;
text-align: center;
margin: 0px -10px 0px -10px;
}
.grid-container > div {
text-align: center;
}
.logos {
margin: 0px 10px 10px 0;
}
.ib {
display: inline-block;
margin: 00px 20px 20px 0px;
}
.logos-container {
margin: 20px 0px 50px 0px;
width: 100%;
float: left;
position: relative;
min-width: 800px;
}
.google-logo {
text-align: center;
position: relative;
}
.video {
margin: 20px 0px 0px 0px;
width: 100%;
float: left;
position: relative;
}
.abstract {
margin: 50px 0px 0px 0px;
width: 100%;
float: left;
position: relative;
}
.data {
margin: 40px 0px 80px 0px;
width: 100%;
float: left;
position: relative;
}
.superhero {
width: 1024px;
position: relative;
margin: auto;
padding-left: 80px;
padding-right: 80px;
overflow: auto;
/* min-width: 800px; */
}
.title {
margin: 50px 0px 0px 0px;
width: 100%;
float: left;
position: relative;
text-align: center;
/* line-height: 40pt; */
}
.title-line {
margin: 20px 0px 20px 0px;
}
.authors {
/* margin: 25px 0px 0px 0px; */
/* width: 400px;
height: 1100px; */
padding-left: 15%;
padding-right: 15%;
/* float: left; */
position: relative;
text-align: center;
}
.paper {
width: 100%;
float: left;
position: relative;
}
h1.title-name {
font-size: 40px;
font-weight: 300;
margin-bottom: 0px;
display: inline-block;
}
h1.name {
font-size: 40px;
font-weight: 300;
margin-bottom: 10px;
display: inline-block;
}
.email {
display: block;
font-size: 19px;
font-weight: 300;
color: #81899C;
margin-top: 0px;
display: inline-block;
}
.lead {
font-size: 20px;
font-weight: 300;
margin-top: 0px;
line-height: 30px;
display: inline-block;
}
.names {
font-size: 1.05em;
font-weight: 300;
margin-top: 0px;
line-height: 20pt;
display: inline-block;
text-align: center;
}
.video-container {
position: relative;
padding-bottom: 56.25%; /* 16:9 */
height: 0;
}
.video-container iframe {
position: absolute;
top: 0;
left: 0;
width: 100%;
height: 100%;
}
.footer {
width: 100%;
height: 65px;
float: left;
margin-top: 25px;
}
.footer-googleai {
width: 20%;
float: left;
}
.footer-google {
width: 20%;
float: right;
text-align: right;
}
a.pagelink:link,
a.pagelink:visited,
a.pagelink:active { color: #81899C; text-decoration: none; }
a.pagelink:hover { color: #006699; text-decoration: underline; }
</style>
<body>
<div class="superhero">
<div class="title">
<h1 class="title-name"><strong>Barbershop:</strong></h1>
<h2>GAN-based Image Compositing using Segmentation Masks</h2>
<div class="title-line">
<hr style = "width: 32%;">
</div>
</div>
<div class ="authors">
<h2 class="names"><a href="https://github.com/ZPdesu"> Peihao Zhu</a>,
<a href="https://github.com/RameenAbdal"> Rameen Abdal</a>,
<a href="https://scholar.google.com/citations?user=rS1xJIIAAAAJ&hl=en"> John Femiani</a>,
<a href="http://peterwonka.net/"> Peter Wonka</a></h2>
</div>
<div class="logos-container">
<div class ="google-logo">
<h2 class="names"> <a href="https://arxiv.org/abs/2106.01505">arXiv</a> <a href="https://github.com/ZPdesu/Barbershop">Code</a></h2>
</div>
</div>
<div class="paper">
<div class="grid-container">
<div class="item1"><a href="Barbershop.pdf"><img src="thumbs/page-01.png" class="paper-thumbnail"></a></div>
<div class="item2"><a href="Barbershop.pdf"><img src="thumbs/page-04.png" class="paper-thumbnail"></a></div>
<div class="item3"><a href="Barbershop.pdf"><img src="thumbs/page-08.png" class="paper-thumbnail"></a></div>
<div class="item4"><a href="Barbershop.pdf"><img src="thumbs/page-09.png" class="paper-thumbnail"></a></div>
</div>
<br>
Click to view the paper.
</div>
<div class="video">
<h2 class="section-title">Video</h2>
<div class="video-container" style="margin-top: 50px;">
<iframe width="560" height="315" src="https://www.youtube.com/embed/ZU-yrAvoJfQ" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<!-- <iframe width="560" height="315" src="https://www.youtube.com/embed/ZU-yrAvoJfQ" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> -->
</div>
</div>
<div class="abstract">
<h2>Abstract</h2>
<p style="text-align: justify;">
<span class="first-letter">S</span>eamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different parts of the image. Even though recent work on GANs enables synthesis of realistic hair or faces, it remains difficult to combine them into a single, coherent, and plausible image rather than a disjointed set of image patches. We present a novel solution to image blending, particularly for the problem of hairstyle transfer, based on GAN-inversion. We propose a novel latent space for image blending which is better at preserving detail and encoding spatial information, and propose a new GAN-embedding algorithm which is able to slightly modify images to conform to a common segmentation mask. Our novel representation enables the transfer of the visual properties from multiple reference images including specific details such as moles and wrinkles, and because we do image blending in a latent-space we are able to synthesize images that are coherent. Our approach avoids blending artifacts present in other approaches and finds a globally consistent image. Our results demonstrate a significant improvement over the current state of the art in a user study, with users preferring our blending solution over 95 percent of the time.</p>
</div>
<br>
<div class="section list" >
<h2>BibTex</h2>
<div class="section bibtex">
<pre>@misc{zhu2021barbershop,
title={Barbershop: GAN-based Image Compositing using Segmentation Masks},
author={Peihao Zhu and Rameen Abdal and John Femiani and Peter Wonka},
year={2021},
eprint={2106.01505},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
</pre>
</div>
</div>
</div>
</body>