-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.html
1727 lines (1250 loc) · 63.9 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
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
<!DOCTYPE html>
<html style="font-size:100%">
<head>
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1" />
<title>Noam Aigerman's Homepage</title>
<script type="text/javascript" src="html/jquery/jquery.min.js"></script>
<script type="text/javascript" src="html/jquery/jquery-ui.min.js"></script>
<link rel="stylesheet" type="text/css" href="html/jquery/jquery-ui.min.css"/>
<link href="https://fonts.googleapis.com/css2?family=Open+Sans:wght@300&display=swap" rel="stylesheet">
<script type="text/javascript" src="html/JS/setMail.js?2"></script>
<script type="text/javascript">
// function setVline(e){
// a=$('.vline').first();
// p=$('.paper-entry').last();
// t=a.offset().top;
// b=p.offset().top + p.outerHeight(true);
// a.height(b-t-20);
// a.css("left", p.position().left-20);
// }
// $(window).resize(setVline);
function setTooltip(){
$('.paper-link').each(
function(){
$(this).tooltip({tooltipClass:'paper-size-tooltip',content: function() {
var element = $( this );
if ( element.is( "[data-size]" ) ) {
return element.attr( "data-size" )+ ' MB';
}
},'position':{my: 'center bottom', at: 'center top',of:$(this)}, hide: {duration:50},show:{duration:10},items:'a'});
}
);
$('.teaser').each(
function(){
var parent=$(this);//.parent();
$(this).tooltip({
'position':{my: 'left top', at: 'left bottom',of:$(this)}, hide: {duration:0},tooltipClass:'teaser-text-tooltip',
content: '<div style="background-color:rgba(255,255,255,0);">'+$(this).attr('title')+'<hr style=color:white;"><span style="font-size:85%;color:rgb(230,230,230)"><span style="text-decoration:underline">Figure:</span> '+$(this).attr('alt')+'</span></div>'
});
}
);
// $('.paper-data > a').attr("target","_blank");
}
// function setEaster(){
// fadeouttime=500;
// fadeintime=6000;
// $('#mepic').hover(
// function(){
// $('#me2d').stop().animate({'opacity':0},fadeintime);
// $('#me2d').promise().done(function(){$('#me3d').stop().animate({'opacity':1},fadeouttime);});
// //$('#me2d').promise().done(function(){$(this).css('display','none');$('#me3d').css('display','inline');});
// },
// function(){$('#me2d').stop().animate({'opacity':1},fadeouttime);
// $('#me3d').stop().animate({'opacity':0},fadeouttime);
// }
// );
// $('#me3d').attr('src','pics/me3d.png');
// }
function setOpacity(){
return;
hideopa=0.7;
fadeint=200;
fadeoutt=500;
//$('.teaser').css('opacity', opa);
// when hover over the selected image change the opacity to 1
$('.teaser').hover(
function(){
$('.teaser').parent().stop().animate({'opacity':hideopa},fadeint); /*,'background-color':'none'*/
$(this).parent().stop().animate({'opacity':1},fadeint);/*,'background-color':'rgb(246,245,244)'*/
},
function(){
$('.teaser').parent().stop().animate({'opacity':1},fadeoutt)/*,'background-color':'none'*/
});
}
function setYears(){
$('li.paperyear').each(function(){
var element = $( this );
if ( element.is( "[year]" ) ) {
element.prepend('<hr class="fancy-line"></hr><div class="tab">'+element.attr('year')+"</div>")
}
});
}
</script>
<link rel="stylesheet" type="text/css" href="html/css/main.css"/>
</head>
<body onload="setMail();setTooltip();setOpacity();
$('.fancy-line').each(function(ind){$(this).delay(ind*250+300).animate({
width:'100%'
},500);
});
" >
<div id = "main_container">
<div id="main">
<div style="display: grid;">
<div id="infobox">
<!-- <div style="display: grid;grid-template-columns: min-content min-content;">
<div class="fancy-border" style="float: left;grid-column: 1;">
<div class="heading title" style="margin-bottom: -8px;white-space: nowrap;">
Noam Aigerman
</div>
</div>
<div style="grid-column: 2;display: flex; align-items: end;">
<span class="pronounce-tip"> (pronounced "Noh-uhm", like Noah with an M at the end.)</span>
</div>
</div> -->
<!-- <div class="fancy-border"> -->
<div id="name">
<span class="fancy-border"><span class="heading title">Noam Aigerman </span></span>
<span class="pronounce-tip"> (pronounced "Noh-uhm", like Noah with an M at the end.)</span>
</div>
<!-- </div> -->
<div>
<div style="clear: both;" class="subheading"><!-- padding-top: 12px; -->
<div id = "affiliations">
<span style="white-space: nowrap;">Assistant Professor,</span> <span style="white-space: nowrap;"><a target="_blank" href="https://www.umontreal.ca/en/">University of Montreal</a></span><br>
<span style="white-space: nowrap;">Associate Academic Member,</span> <span style="white-space: nowrap;"><a target="_blank" href="https://mila.quebec/en/">Mila</a></span>
</div>
<div style="font-size: 70%; padding-top:36px;padding-left: 1px;display: grid; align-items: center;grid-template-columns: min-content auto;">
<!-- <div style=""> -->
<div style=" grid-column: 1">
<a id="email-link" href="noam.aigerman@umontreal.ca">
<svg class="icon" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round">
<title>Email</title>
<path d="M4 4h16c1.1 0 2 .9 2 2v12c0 1.1-.9 2-2 2H4c-1.1 0-2-.9-2-2V6c0-1.1.9-2 2-2z"/>
<polyline points="22,6 12,13 2,6"/>
</svg></a>
</div>
<div style=" grid-column: 2"><span><a href="mailto:noam.aigerman@umontreal.ca">noam.aigerman@umontreal.ca</a></span></div>
<div style="padding-right: 10px; grid-column: 1;">
<a href="https://maps.app.goo.gl/a9y59VGZeBpYYGjN8" target ="_blank"><svg class="icon" role="img" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg">
<title>Google Maps</title>
<path d="M19.527 4.799c1.212 2.608.937 5.678-.405 8.173-1.101 2.047-2.744 3.74-4.098 5.614-.619.858-1.244 1.75-1.669 2.727-.141.325-.263.658-.383.992-.121.333-.224.673-.34 1.008-.109.314-.236.684-.627.687h-.007c-.466-.001-.579-.53-.695-.887-.284-.874-.581-1.713-1.019-2.525-.51-.944-1.145-1.817-1.79-2.671L19.527 4.799zM8.545 7.705l-3.959 4.707c.724 1.54 1.821 2.863 2.871 4.18.247.31.494.622.737.936l4.984-5.925-.029.01c-1.741.601-3.691-.291-4.392-1.987a3.377 3.377 0 0 1-.209-.716c-.063-.437-.077-.761-.004-1.198l.001-.007zM5.492 3.149l-.003.004c-1.947 2.466-2.281 5.88-1.117 8.77l4.785-5.689-.058-.05-3.607-3.035zM14.661.436l-3.838 4.563a.295.295 0 0 1 .027-.01c1.6-.551 3.403.15 4.22 1.626.176.319.323.683.377 1.045.068.446.085.773.012 1.22l-.003.016 3.836-4.561A8.382 8.382 0 0 0 14.67.439l-.009-.003zM9.466 5.868L14.162.285l-.047-.012A8.31 8.31 0 0 0 11.986 0a8.439 8.439 0 0 0-6.169 2.766l-.016.018 3.665 3.084z"/>
</svg>
</div>
<div id="address" style="grid-column: 2;">
<span style="font-weight: bold;">Room 3359</span>,
Pavillon André-Aisenstadt
<br>C.P. 6128, succ. Centre-Ville, Montréal, Québec, Canada H3C 3J7
</div></a>
<!-- </div> -->
<div style=" grid-column: 1">
<a href="https://scholar.google.com/citations?user=eO2xkdMAAAAJ&hl=en" target="_blank" >
<svg class="icon" role="img" viewBox="0 0 25 25" xmlns="http://www.w3.org/2000/svg">
<title>Google Scholar</title>
<path d="M5.242 13.769L0 9.5 12 0l12 9.5-5.242 4.269C17.548 11.249 14.978 9.5 12 9.5c-2.977 0-5.548 1.748-6.758 4.269zM12 10a7 7 0 1 0 0 14 7 7 0 0 0 0-14z"/>
</svg></a>
</div>
<div style=" grid-column: 2">
<a href="https://scholar.google.com/citations?user=eO2xkdMAAAAJ&hl=en" target="_blank" >
Google Scholar</a>
</div>
<div style=" grid-column: 1">
<a href="https://twitter.com/AigermanNoam" target="_blank">
<svg class="icon" role="img" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg">
<title>Twitter</title>
<path d="M23.953 4.57a10 10 0 01-2.825.775 4.958 4.958 0 002.163-2.723c-.951.555-2.005.959-3.127 1.184a4.92 4.92 0 00-8.384 4.482C7.69 8.095 4.067 6.13 1.64 3.162a4.822 4.822 0 00-.666 2.475c0 1.71.87 3.213 2.188 4.096a4.904 4.904 0 01-2.228-.616v.06a4.923 4.923 0 003.946 4.827 4.996 4.996 0 01-2.212.085 4.936 4.936 0 004.604 3.417 9.867 9.867 0 01-6.102 2.105c-.39 0-.779-.023-1.17-.067a13.995 13.995 0 007.557 2.209c9.053 0 13.998-7.496 13.998-13.985 0-.21 0-.42-.015-.63A9.935 9.935 0 0024 4.59z"/>
</svg></a>
</div>
<div style=" grid-column: 2">
<a href="https://twitter.com/AigermanNoam" target="_blank">
Twitter
</div>
<div style=" grid-column: 1">
<a href = "https://outlook.office365.com/calendar/published/bfb42cda911e483c804e1aa24b7005d5@umontreal.ca/9effdc18dae74e6d9048daaeaf1440db12973665910407921392/calendar.html" target="_blank">
<svg class="icon" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://creativecommons.org/ns#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:svg="http://www.w3.org/2000/svg" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 45 45" style="enable-background:new 0 0 45 45;" xml:space="preserve" version="1.1" id="svg2"><metadata id="metadata8"><rdf:RDF><cc:Work rdf:about=""><dc:format>image/svg+xml</dc:format><dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/></cc:Work></rdf:RDF></metadata><defs id="defs6"><clipPath id="clipPath18" clipPathUnits="userSpaceOnUse"><path id="path20" d="M 0,36 36,36 36,0 0,0 0,36 Z"/></clipPath><clipPath id="clipPath30" clipPathUnits="userSpaceOnUse"><path id="path32" d="M 6,32 C 3.791,32 2,30.209 2,28 L 2,28 2,4 C 2,1.791 3.791,0 6,0 l 0,0 24,0 c 2.209,0 4,1.791 4,4 l 0,0 0,24 c 0,2.209 -1.791,4 -4,4 l 0,0 -24,0 z"/></clipPath><clipPath id="clipPath40" clipPathUnits="userSpaceOnUse"><path id="path42" d="M 0,36 36,36 36,0 0,0 0,36 Z"/></clipPath></defs><g transform="matrix(1.25,0,0,-1.25,0,45)" id="g10"><path id="path12" style="stroke-width:1px" d="m 28.814,29.609 1.996,0 0,2.391 -1.996,0 0,-2.391 z"/><g id="g14"><g clip-path="url(#clipPath18)" id="g16"><g transform="translate(30,32)" id="g22"><path id="path24" style="stroke-width:1px" d="m 0,0 -24,0 c -2.209,0 -4,-1.791 -4,-4 l 0,-24 c 0,-2.209 1.791,-4 4,-4 l 24,0 c 2.209,0 4,1.791 4,4 L 4,-4 C 4,-1.791 2.209,0 0,0"/></g></g></g><g id="g26"><g clip-path="url(#clipPath30)" id="g28"><path id="path34" style="stroke-width:1px" d="m 34,23 -32,0 0,9 32,0 0,-9 z"/></g></g><g id="g36"><g clip-path="url(#clipPath40)" id="g38"><g transform="translate(8.8359,27.2695)" id="g44"><path id="path46" style="stroke-width:1px" d="m 0,0 c -0.702,0 -1.271,0.666 -1.271,1.489 0,0.823 0.569,1.49 1.271,1.49 0.701,0 1.27,-0.667 1.27,-1.49 C 1.27,0.666 0.701,0 0,0"/></g><g transform="translate(9.543,28.917)" id="g48"><path id="path50" style="stroke-width:1px" d="m 0,0 c -0.055,0.479 -0.374,0.792 -0.729,1.017 -0.485,0.306 -1,1.007 -1,1.876 0,1.105 0.671,2.095 1.5,2.095 0.83,0 1.5,-0.905 1.5,-1.905 l 1.997,0 c -0.021,2 -1.576,3.821 -3.497,3.821 -1.933,0 -3.5,-1.819 -3.5,-4.005 0,-1.853 1.045,-3.371 2.57,-3.925 C -0.4,-1.302 0.064,-0.579 0,0"/></g><g transform="translate(14.8359,27.2695)" id="g52"><path id="path54" style="stroke-width:1px" d="m 0,0 c -0.702,0 -1.271,0.666 -1.271,1.489 0,0.823 0.569,1.49 1.271,1.49 0.701,0 1.27,-0.667 1.27,-1.49 C 1.27,0.666 0.701,0 0,0"/></g><g transform="translate(15.543,28.917)" id="g56"><path id="path58" style="stroke-width:1px" d="m 0,0 c -0.055,0.479 -0.374,0.792 -0.729,1.017 -0.485,0.306 -1,1.007 -1,1.876 0,1.105 0.671,2.095 1.5,2.095 0.83,0 1.5,-0.905 1.5,-1.905 l 1.997,0 c -0.021,2 -1.576,3.821 -3.497,3.821 -1.933,0 -3.5,-1.819 -3.5,-4.005 0,-1.853 1.045,-3.371 2.57,-3.925 C -0.4,-1.302 0.064,-0.579 0,0"/></g><g transform="translate(20.8359,27.2695)" id="g60"><path id="path62" style="stroke-width:1px" d="m 0,0 c -0.702,0 -1.271,0.666 -1.271,1.489 0,0.823 0.569,1.49 1.271,1.49 0.701,0 1.27,-0.667 1.27,-1.49 C 1.27,0.666 0.701,0 0,0"/></g><g transform="translate(21.543,28.917)" id="g64"><path id="path66" style="stroke-width:1px" d="m 0,0 c -0.055,0.479 -0.374,0.792 -0.729,1.017 -0.485,0.306 -1,1.007 -1,1.876 0,1.105 0.671,2.095 1.5,2.095 0.83,0 1.5,-0.905 1.5,-1.905 l 1.997,0 c -0.021,2 -1.576,3.821 -3.497,3.821 -1.933,0 -3.5,-1.819 -3.5,-4.005 0,-1.853 1.045,-3.371 2.57,-3.925 C -0.4,-1.302 0.064,-0.579 0,0"/></g><g transform="translate(26.8359,27.2695)" id="g68"><path id="path70" style="stroke-width:1px" d="m 0,0 c -0.702,0 -1.271,0.666 -1.271,1.489 0,0.823 0.569,1.49 1.271,1.49 0.701,0 1.27,-0.667 1.27,-1.49 C 1.27,0.666 0.701,0 0,0"/></g><g transform="translate(27.543,28.917)" id="g72"><path id="path74" style="stroke-width:1px" d="m 0,0 c -0.055,0.479 -0.374,0.792 -0.729,1.017 -0.485,0.306 -1,1.007 -1,1.876 0,1.105 0.671,2.095 1.5,2.095 0.83,0 1.5,-0.905 1.5,-1.905 l 1.997,0 c -0.021,2 -1.576,3.821 -3.497,3.821 -1.933,0 -3.5,-1.819 -3.5,-4.005 0,-1.853 1.045,-3.371 2.57,-3.925 C -0.4,-1.302 0.064,-0.579 0,0"/></g><path id="path76" style="stroke-width:1px" d="m 15,17 -4,0 0,4 4,0 0,-4 z"/><path id="path78" style="stroke-width:1px" d="m 20,17 -4,0 0,4 4,0 0,-4 z"/><path id="path80" style="stroke-width:1px" d="m 25,17 -4,0 0,4 4,0 0,-4 z"/><path id="path82" style="stroke-width:1px" d="m 30,17 -4,0 0,4 4,0 0,-4 z"/><path id="path84" style="stroke-width:1px" d="m 10,12 -4,0 0,4 4,0 0,-4 z"/><path id="path86" style="stroke-width:1px" d="m 15,12 -4,0 0,4 4,0 0,-4 z"/><path id="path88" style="stroke-width:1px" d="m 20,12 -4,0 0,4 4,0 0,-4 z"/><path id="path90" style="stroke-width:1px" d="m 25,12 -4,0 0,4 4,0 0,-4 z"/><path id="path92" style="stroke-width:1px" d="m 30,12 -4,0 0,4 4,0 0,-4 z"/><path id="path94" style="stroke-width:1px" d="m 10,7 -4,0 0,4 4,0 0,-4 z"/><path id="path96" style="stroke-width:1px" d="m 15,7 -4,0 0,4 4,0 0,-4 z"/><path id="path98" style="stroke-width:1px" d="m 20,7 -4,0 0,4 4,0 0,-4 z"/><path id="path100" style="stroke-width:1px" d="m 25,7 -4,0 0,4 4,0 0,-4 z"/><path id="path102" style="stroke-width:1px" d="m 30,7 -4,0 0,4 4,0 0,-4 z"/><path id="path104" style="stroke-width:1px" d="M 10,2 6,2 6,6 10,6 10,2 Z"/><path id="path106" style="stroke-width:1px" d="m 15,2 -4,0 0,4 4,0 0,-4 z"/><path id="path108" style="stroke-width:1px" d="m 20,2 -4,0 0,4 4,0 0,-4 z"/></g></g></g></svg></a>
</div>
<div style=" grid-column: 2">
<a href = "https://outlook.office365.com/calendar/published/bfb42cda911e483c804e1aa24b7005d5@umontreal.ca/9effdc18dae74e6d9048daaeaf1440db12973665910407921392/calendar.html" target="_blank">Calendar</a>
</div>
<!-- <iframe src= "https://outlook.office365.com/calendar/published/bfb42cda911e483c804e1aa24b7005d5@umontreal.ca/9effdc18dae74e6d9048daaeaf1440db12973665910407921392/calendar.html" style="border: 0;-webkit-transform:scale(0.7);-moz-transform-scale(0.7);" width="800" height="600" frameborder="0" scrolling="no"></iframe> -->
</div>
</div>
<br>
</div>
<br>
<div id="about">
<span style="text-decoration: underline;"></span> I am a computer scientist working on problems related to machine learning and 3D geometry. My research lies at the intersection of <span style="font-style: italic;">geometry processing</span>, <span style="font-style: italic;">computer graphics</span>, <span style="font-style: italic;">deep learning</span>, and <span style="font-style: italic;">optimization</span>. Currently, I mostly focus on using geometry processing to devise thoeretically-grounded machine learning approaches for 3D problems; and, vice-versa, approaching geometry processing tasks from a machine learning perspective.
</div>
</div>
<div id="mebox">
<div id="mepic">
<img id="me2d" src="pics/me.jpg" alt="Yes, this is I!" class="round-corner" />
</div>
</div>
</div>
<br/>
<div id="pub" style="padding-top:20px">
<div class="fancy-border">
<span class="heading">Teaching</span>
</div>
<br/>
</div>
<div>
Winter 2024: <a href="course_NGP.html" target ="_blank">IFT6095 - Neural Geometry Processing</a>
</div>
<div style="clear:both">
</div>
<br><br>
<div id="pub" style="padding-top:20px">
<div class="fancy-border">
<span class="heading">Publications</span>
 
<span id="hoverhint" class="subheading" style="white-space: nowrap;"> (hover over a project's image for a one-sentence summary)</span>
</div>
<br/>
<div class="paper-grid" style="padding-top:5px">
<img alt="Top: point clouds are generated through a pretrained generative model, and are used to deform and swap meshes (bottom)." class="teaser" src="html/deformation_explore.PNG" title="Using an existing generative model for point clouds to generat and control deformations of meshes."/>
<div class="paper-cell">
<div class="paper-title">
Explorable Mesh Deformation Subspaces from Unstructured 3D Generative Models
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Arman Maesumi,
</span>
<span style="white-space: nowrap;">
Paul Guerrero,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Matthew Fisher,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Daniel Ritchie
</span>
</div>
<div class = "venue">
ACM SIGGRAPH Asia 2023
</div>
<div class="paper-links">
<a href="https://armanmaesumi.github.io/explorable_subspaces/" target="_blank">Project page</a>
</div>
</div>
</div>
<img alt="The cow is deformed into two desired shapes described by a text prompt, in this case a turtle and a stag." class="teaser" src="html/textdeformer.jpg" title="Deforming 3D meshes based on text prompts, by rendering the mesh from various view angles and using a trained visual encoder (CLIP), with a tailor-made deformation module which can consolidate the different viewpoints in a meaningful way."/>
<div class="paper-cell">
<div class="paper-title">
TextDeformer: Geometry Manipulation using Text Guidance
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
William Gao,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Thibault Groueix,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Rana Hanocka
</span>
</div>
<div class = "venue">
ACM SIGGRAPH 2023
</div>
<div class="paper-links">
<a href="https://threedle.github.io/TextDeformer/" target="_blank">Project page</a>
</div>
</div>
</div>
<img alt="Face meshes from various datasets, with different triangulations, can be automatically deformed by our network into two facial expressions." class="teaser" src="html/NFR.jpg" title="Using a neural network to deform arbitrary facial meshes, w.r.t. human-interpretable parameters which can enable artists to directly control and manipulate the expression in a plausible manner."/>
<div class="paper-cell">
<div class="paper-title">
Neural Face Rigging for Animating and Retargeting Facial Meshes in the Wild
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Dafei Qin,
</span>
<span style="white-space: nowrap;">
Jun Saito,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Thibault Groueix,
</span>
<span style="white-space: nowrap;">
Taku Komura
</span>
</div>
<div class = "venue">
ACM SIGGRAPH 2023
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2305.08296" target="_blank">Paper</a>
</div>
</div>
</div>
<img alt="A coarse mesh is progressively refined using a neural network, given additional details transmitted." class="teaser" src="html/neural_progressive.jpg" title="Compressing a mesh, by encoding it as coarse mesh and neural features, enabling to progressively refine the coarse mesh as additional features are transmitted."/>
<div class="paper-cell">
<div class="paper-title">
Neural Progressive Meshes
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Yun-Chun Chen,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Alec Jacobson
</span>
</div>
<div class = "venue">
ACM SIGGRAPH 2023
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2308.05741" target="_blank">Paper</a>
</div>
</div>
</div>
<img alt="A point is selected on the mesh by a user, and a region containing this point is selected by our network, such that the region can UV-mapped with low-distortion (UV map visualized with a square texture on the selected region)." class="teaser" src="html/DAWand.jpg" title="Using a neural network to segment a region on a mesh containing a given selected point in a manner that is aware of the distortion generated by a UV-mapping algorithm w.r.t. the selected region."/>
<div class="paper-cell">
<div class="paper-title">
DA Wand: Distortion-Aware Selection using Neural Mesh Parameterization
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Richard Liu,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Rana Hanocka
</span>
</div>
<div class = "venue">
CVPR 2023
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2212.06344" target="_blank">Paper</a> |
<a href="https://threedle.github.io/DA-Wand/" target="_blank">Project page</a>
</div>
</div>
</div>
<img alt="Top: our previous method can produce a 1-to-1 UV map of the bunny into the cross, but has distortion and scales some parts of mesh (in red). Bottom: this paper can also compute a 1-to-1 UV map, but also ensure it has low distortion and less scaling." class="teaser" src="html/projects/isoinj/isoinj.jpg" title="An energy that penalizes both lack of injectivity and high isometric distortion at the same time, enabling computation of 1-to-1 and low-distortion maps with arbitrary positional constraints."/>
<div class="paper-cell">
<div class="paper-title">
Isometric Energies for Recovering Injectivity in Constrained Mapping
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Xingyi Du,
</span>
<span style="white-space: nowrap;">
Danny M. Kaufman,
</span>
<span style="white-space: nowrap;">
Qingnan Zhou,
</span>
<span style="white-space: nowrap;">
Shahar Z. Kovalsky,
</span>
<span style="white-space: nowrap;">
Yajie Yan,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Tao Ju
</span>
</div>
<div class = "venue">
ACM SIGGRAPH Asia 2022
</div>
<div class="paper-links">
<a href="https://duxingyi-charles.github.io/publication/isometric-energies-for-recovering-injectivity-in-constrained-mapping/" target="_blank">Project page</a>
</div>
</div>
</div>
<img alt="A chair with parts of it missing (left) is completed by our method to a full chair (middle) by copying and transforming existing parts to missing areas, while competing generative approaches produce fuzzy approximiations (right)." class="teaser" src="html/projects/patch-rd/patch-rd.jpg" title="Training a network to complete missing parts of a shape by copying and transforming existing parts of the input."/>
<div class="paper-cell">
<div class="paper-title">
PatchRD: Detail-Preserving Shape Completion by Learning Patch Retrieval and Deformation
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Bo Sun,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Qixing Huang,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri
</span>
</div>
<div class = "venue">
ECCV 2022
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2207.11790" target="_blank">Paper</a> |
<a href="https://github.com/GitBoSun/PatchRD" target="_blank">Code</a>
</div>
</div>
</div>
<img alt="Our method produces an atlas with a complex topology for a set of shapes." class="teaser" src="html/projects/joint_atlases/joint_atlases.jpg" title="Computing a UV layout for given shapes by representing the map as a mixture of gaussians, enabling defining arbitrary topologies."/>
<div class="paper-cell">
<div class="paper-title">
Learning Joint Surface Atlases
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Theo Deprelle,
</span>
<span style="white-space: nowrap;">
Thibault Groueix,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Mathieu Aubry
</span>
</div>
<div class = "venue">
ECCV Workshop on Learning to Generate 3D Shapes and Scenes, 2022
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2206.06273" target="_blank">Paper</a> |
<a href="https://github.com/TheoDEPRELLE/Joint-Atlas-Surfaces" target="_blank">Code</a>
</div>
</div>
</div>
<img alt="left: a UV map predicted by the network, almost identical to the ground-truth. Right: the network correctly reposes the bunny to the poses demonstrated by the human." class="teaser" src="html/projects/NJF/NJF.jpg" title="A framework for learning to deform meshes in a highly detail-preserving manner, without being tied to a specific mesh."/>
<div class="paper-cell">
<div class="paper-title">
Neural Jacobian Fields: Learning Intrinsic Mappings of Arbitrary Meshes
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Kunal Gupta,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri,
</span>
<span style="white-space: nowrap;">
Jun Saito,
</span>
<span style="white-space: nowrap;">
Thibault Groueix
</span>
</div>
<div class = "venue">
ACM SIGGRAPH 2022 (journal track)
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2205.02904" target="_blank">Paper</a> |
<a href="https://github.com/ThibaultGROUEIX/NeuralJacobianFields" target="_blank">Code</a>
</div>
</div>
</div>
<img alt="The framework learns to represent a surface map from a coarse atlasnet-like MLP composed with a CNN that adds details" class="teaser" src="html/projects/cnnmaps/cnnmaps.jpg" title="Extension of Neural Surface Maps, which decomposes coarse/fine features to an AtlasNet-like representation along with a CNN which adds details."/>
<div class="paper-cell">
<div class="paper-title">
Neural Convolutional Surfaces
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Luca Morreale,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Paul Guerrero,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Niloy Mitra
</span>
</div>
<div class = "venue">
CVPR 2022
</div>
<div class="paper-links">
<a href="http://geometry.cs.ucl.ac.uk/projects/2022/cnnmaps/" target="_blank">Project Page </a>
</div>
</div>
</div>
<img alt="Various poses (orange) generated by our method from a few landmark poses (gray)." class="teaser" src="html/projects/glass/glass.jpg" title="Learning to generate meaningful shape deformations from a (very) sparse set of example deformations."/>
<div class="paper-cell">
<div class="paper-title">
GLASS: Geometric Latent Augmentation for Shape Spaces
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Sanjeev Muralikrishnan,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Matthew Fisher,
</span>
<span style="white-space: nowrap;">
Niloy Mitra
</span>
</div>
<div class = "venue">
CVPR 2022
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2108.03225" target="_blank">Paper </a>
</div>
</div>
</div>
<img alt="A mesh (right) generated by optimizing the alignment of its edges to the input vector field (left)." class="teaser" src="html/diff_tri.jpg" title="A continuous representation of the space of triangulations using 2D power diagrams, enabling using gradient-descent methods (namely within the context of deep learning) to optimize and learn triangulations."/>
<div class="paper-cell">
<div class="paper-title">
Differentiable Surface Triangulation
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Marie-Julie Rakotosaona,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Niloy Mitra,
</span>
<span style="white-space: nowrap;">
Maks Ovsjanikov,
</span>
<span style="white-space: nowrap;">
Paul Guerrero
</span>
</div>
<div class = "venue">
ACM SIGGRAPH ASIA 2021
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2109.10695" target="_blank">Paper </a> |
<a href="https://github.com/mrakotosaon/diff-surface-triangulation" target="_blank">Code</a>
</div>
</div>
</div>
<img alt="A mesh (left) is paramterized to an initial parameterization (middle) with local inversions of triangles and global overlaps of the boundary, which are then alleviated through our optimization (right). " class="teaser" src="html/opt_global_inj.jpg" title="A smooth energy that when optimized yields globally-injective parameterizations (without triangles folding over and without parts of the boundaries overlapping one another)."/>
<div class="paper-cell">
<div class="paper-title">
Optimizing Global Injectivity for Constrained Parameterization
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Xingyi Du,
</span>
<span style="white-space: nowrap;">
Danny M. Kaufman,
</span>
<span style="white-space: nowrap;">
Qingnan Zhou,
</span>
<span style="white-space: nowrap;">
Shahar Z. Kovalsky,
</span>
<span style="white-space: nowrap;">
Yajie Yan,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Tao Ju
</span>
</div>
<div class = "venue">
ACM SIGGRAPH ASIA 2021
</div>
<div class="paper-links">
<a href="https://duxingyi-charles.github.io/publication/optimizing-global-injectivity-for-constrained-parameterization/" target="_blank">Project Page </a>
</div>
</div>
</div>
<img alt="A sequence of reconstructed surfaces using our algorithm, exhibiting good consistent correspondences between each frame in the sequence them (visualized via texture that exhibits the correspondence)." class="teaser" src="html/temporal.jpg" title="Given a sequence of points clouds representing a motion of a shape, this algorithm reconstructs a sequence of surfaces that lie in good correspondence with one another (e.g., head in frame 1 corresponds to head in frame 2)."/>
<div class="paper-cell">
<div class="paper-title">
Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Jan Bednarik,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri,
</span>
<span style="white-space: nowrap;">
Shaifali Parashar,
</span>
<span style="white-space: nowrap;">
Mathieu Salzmann,
</span>
<span style="white-space: nowrap;">
Pascal Fua,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman
</span>
</div>
<div class = "venue">
ICCV 2021
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2104.06950" target="_blank">Paper </a> |
<a href="https://youtu.be/jfNQPTsbM3g" target="_blank">Video</a>
</div>
</div>
</div>
<img alt="A 2D brush is swept along a spiraling trajectory (left), tracing the golden horn (right)." class="teaser" src="html/sweep.jpg" title="An algorithm for robustly computing the total volume occupied by a shape as it's moving along a trajectory."/>
<div class="paper-cell">
<div class="paper-title">
Swept Volumes via Spacetime Numerical Continuation
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Silvia Sellán,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Alec Jacobson
</span>
</div>
<div class = "venue">
ACM SIGGRAPH 2021
</div>
<div class="paper-links">
<a href="https://www.dgp.toronto.edu/projects/swept-volumes/" target="_blank">Project Page </a>
</div>
</div>
</div>
<img alt="Coarse voxel grids (red) are refined into different types of plants (yellow), based on the input desired style (green)." class="teaser" src="html/decorgan2.jpg" title="Training a GAN to upsample coarse voxel grids, conditioned on a desired style, to create realistic high-resolution models."/>
<div class="paper-cell">
<div class="paper-title">
DECOR-GAN: 3D Shape Detailization by Conditional Refinement
</div>
<div class="paper-data">
<div class="authors">
<span style="white-space: nowrap;">
Zhiqin Chen,
</span>
<span style="white-space: nowrap;">
Vladimir G. Kim,
</span>
<span style="white-space: nowrap;">
Matthew Fisher,
</span>
<span style="white-space: nowrap;" class="hi">
Noam Aigerman,
</span>
<span style="white-space: nowrap;">
Hao Zhang,
</span>
<span style="white-space: nowrap;">
Siddhartha Chaudhuri
</span>
</div>
<div class = "venue">
CVPR 2021 (oral)
</div>
<div class="paper-links">
<a href="https://arxiv.org/abs/2012.09159" target="_blank">Paper</a> |
<a href="https://github.com/czq142857/DECOR-GAN" target="_blank">Code</a>
</div>
</div>
</div>
<img alt="Two surfaces are repsented as 2D-to-3D maps via two overfitted neural networks. Since they are both differentiable,this in turn enables optimizing a surface-to-surface map (via h) in a completely differentiable manner." class="teaser" src="html/neural_surface_maps.jpg" title="Representing surface maps as neural networks, and optimizing differentiable composition of such maps to compute mappings between surfaces which minimize distortion."/>
<div class="paper-cell">
<div class="paper-title">
Neural Surface Maps
</div>
<div class="paper-data">
<div class="authors">