-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathFangWan.htm
More file actions
427 lines (356 loc) · 15.9 KB
/
FangWan.htm
File metadata and controls
427 lines (356 loc) · 15.9 KB
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
<!DOCTYPE html>
<HTML>
<HEAD>
<META content="IE=5.0000" http-equiv="X-UA-Compatible">
<META name="description" content="Fang Wan's home page">
<META http-equiv="Content-Type" content="text/html; charset=gb2312">
<LINK href="WanFang_files/wfdoc.css"
rel="stylesheet" type="text/css">
<TITLE>Fang Wan</TITLE>
<META name="GENERATOR" content="MSHTML 11.00.10570.1001">
</HEAD>
<BODY>
<DIV id="layout-content" style="margin-top: 25px;">
<TABLE>
<TBODY>
<TR>
<TD width="670">
<DIV id="toptitle">
<H1>Fang Wan </H1></DIV>
<H3>Assistant Professor</H3>
<P>Room 273, A2 Building
<BR>School of Computer Science and Technology
<BR>University of Chinese Academy of Sciences
<BR>Beijing, China, 101408.
<BR>
<BR> Email:
<A href="mailto:wanfang@ucas.ac.cn"> wanfang@ucas.ac.cn</A>;
<BR> Github:
<A href="https://github.com/Winfrand/">https://github.com/WanFang13/</A>
<BR><BR></P>
</TD>
<TD>
<IMG width="200" src="WanFang_files/WanFang.jpg" border="0">
</TD>
</TR>
<TR></TR></TBODY>
</TABLE>
<DIV id="layout-content" style="margin-top: 25px;">
<H2>Biography</H2>
<P> I am an assistant professor at the <A href="https://scce.ucas.ac.cn/index.php/en/">School of Computer Science and Technology</A>, <A href="http://english.ucas.ac.cn/">University of Chinese Academy of Sciences </A> since 2021.12. From 2019.07 to 2021.12, I was a postdoctor of computer science and technology advised by <A href="http://people.ucas.ac.cn/~0003060?language=en">Prof. Qingming Huang</A>. I got my Ph.D. and Master Degree in 2019 and 2016 respectively at <A href="https://ucassdl.cn">PRISDL</A> in the <A href="https://eece.ucas.ac.cn/index.php/en/">School of Electronic, Electrical and Communication Engineering</A>, <A href="https://english.ucas.ac.cn">University of Chinese Academy of Sciences</A>, advised by <A href="http://people.ucas.ac.cn/~0007279?language=en">Prof. Qixiang Ye</A>.
</P>
<P>My research interests include computer vision and machine learning, specifically for weakly supervised learning and visual object detection.</P>
<H2>News</H2>
<UL>
<LI>
Jul. 2023: Two papers are accepted by ICCV 2023, Con! [Liu and Zhao]
</LI>
<LI>
May. 2023: One paper is accepted by TPAMI 2023.
</LI>
<LI>
Nov. 2022: One paper is accepted by TNNLS 2022, Con! [Yuan]
</LI>
<LI>
May 2022: One paper is accepted by ECCV 2022, Con! [Mingxiang]
</LI>
<LI>
March. 2022: One paper is accepted by CVPR 2022, Con! [Tianning]
</LI>
<LI>
March. 2021: One paper is accepted by ICCV 2021, Con! [Wei]
</LI>
<LI>
Dec. 2020: Two papers are accepted by AAAI 2021, Con! [Mengying]
</LI>
<LI>
Aug. 2020: The pytorch version of CMIL is avalable at <A href="https://github.com/shenyunhang/DRN-WSOD">[here]</A>. Thanks for the contribution of <A href="https://github.com/shenyunhang">shenyunhang
</LI>
<LI>
Jul. 2020: I have won the "Top 100 Doctoral Thesis" of CAS!
</LI>
<LI>
Sep. 2019: Our paper <A href="https://github.com/zhangxiaosong18/FreeAnchor">[FreeAnchor]</A> is accepted by NeurIPS 2019.
</LI>
<LI>
Jul. 2019: Two papers are accepted by ICCV 2019, Con! [Haolan and Yan & Xiaobo]
</LI>
<LI>
Jun. 2019: We won the CVPR 2019 SkelNetOn 2019, Con! [Chang]
</LI>
<LI>
Apr. 2019: A simplified version of MELM with context in PyTorch is released <A href="https://github.com/vasgaowei/pytorch_MELM">[here]</A>.
</LI>
<LI>
Feb. 2019: The slides of "Weakly Supervised Object Detection Localization and Instance Segmentation" in the report of VLASE 2019-02-27 is avalable at <A href="https://github.com/Winfrand/Winfrand.github.io/raw/master/Weakly%20Supervised%20DLIS-TalkVersion.pdf">[WS-DLIS.pdf]</A>
</LI>
<LI>
Feb. 2019: Our paper "Min-Entropy Latent Model for Weakly Supervised Object Detection" has been accepted by IEEE TPAMI 2019.
</LI>
<LI>
Feb. 2019: Three of our papers have been accepted by CVPR 2019.
</LI>
<LI>
Dec. 2018: The code for our CVPR 2018 paper <A href="https://ucassdl.cn/downloads/publication/CVPR2018_WanFang.pdf">"Min-Entropy Latent Model for Weakly Supervised Object Detection"</A> is available at <A href="https://github.com/Winfrand/MELM">"https://github.com/Winfrand/MELM"</A>.
</LI>
</UL>
<H2>Publications</H2>
<table class="pub_table">
<tbody>
<!-- #20 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ICCV2023-GPM.png" class="papericon"></td>
<td
class="pub_td2"> Yuzhong Zhao, Qixiang Ye, Weijia Wu, Chunhua Shen and <u>Fang Wan</u>
<br><b>Generative Prompt Model for Weakly Supervised Object Localization</b>
<br>IEEE International Conference on Computer Vision (ICCV), 2023
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #19 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ICCV2023-imTED.png" class="papericon"></td>
<td
class="pub_td2">Feng Liu, Xiaosong Zhang, Zhiliang Peng, Zonghao Guo, <u>Fang Wan</u>, Xiangyang Ji and Qixiang Ye
<br><b>Integrally Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection </b>
<br>IEEE International Conference on Computer Vision (ICCV), 2023
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #18 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/TPAMI-2023-MIDL.png" class="papericon"></td>
<td
class="pub_td2"><u>F Wan</u>, Q Ye, T Yuan, S Xu, J Liu, X Ji, Q Huang
<br><b>Multiple Instance Differentiation Learning for Active Object Detection</b>
<br>IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #17 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/CVPR2023-AttentionShift.png" class="papericon"></td>
<td
class="pub_td2">M Liao, Z Guo, Y Wang, P Yuan, B Feng and <u>F Wan</u>
<br><b>AttentionShift: Iteratively Estimated Part-Based Attention Map for Pointly Supervised Instance Segmentation</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #16 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ECCV2022-SPE.png" class="papericon"></td>
<td
class="pub_td2">M Liao, <u>F Wan</u>, Y Yao, Z Han, J Zou, Y Wang, B Feng, P Yuan and Q Ye
<br><b>End-to-End Weakly Supervised Object Detection with Sparse Proposal Evolution</b>
<br>European Conference on Computer Vision, 2022
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #15 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/TGRS-APL.png" class="papericon"></td>
<td
class="pub_td2">S Wang, B Du, D Zhang and <u>F Wan</u>
<br><b>Adversarial prototype learning for hyperspectral image classification</b>
<br>IEEE Transactions on Geoscience and Remote Sensing, 2021
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #14 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/TCSVT-DC.png" class="papericon"></td>
<td
class="pub_td2">F Liu, X Zhang, <u>F Wan</u>, X Ji and Q Ye
<br><b>Domain contrast for domain adaptive object detection</b>
<br>IEEE Transactions on Circuits and Systems for Video Technology, 2021
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #13 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/TNNLS-PST.png" class="papericon"></td>
<td
class="pub_td2">B Yang, <u>F Wan</u>, C Liu, B Li, X Ji and Q Ye
<br><b>Part-based semantic transform for few-shot semantic segmentation</b>
<br>IEEE Transactions on Neural Networks and Learning Systems, 2021
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #12 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/AAAI-NCE-Net-short.png" class="papericon"></td>
<td
class="pub_td2"><u>Fang Wan</u>, Tianning Yuan, Mengying Fu, Xiangyang Ji, Qingming Huang and Qixiang Ye
<br><b>Nearest Neighbor Classifier Embedded Network for Active Learning</b>
<br>Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #11 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/AAAI-ADS.png" class="papericon"></td>
<td
class="pub_td2">Mengying Fu, Tianning Yuan, <u>Fang Wan</u>, Songcen Xu, and Qixiang Ye
<br><b>Agreement-Discrepancy-Selection: Active Learning with Progressive Distribution Alignment</b>
<br>Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021
<br>
[<a href="">PDF</a>]
[<a href="">Code</a>]
</td>
</tr>
<!-- #10 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/NIPS2019.png" class="papericon"></td>
<td
class="pub_td2">Xiaosong Zhang, <u>Fang Wan</u>, Chang Liu, Rongrong Ji and Qixiang Ye
<br><b>FreeAnchor: Learning to Match Anchors for Visual Object Detection</b>
<br>Neural Information Processing Systems (NeurIPS), 2019
<br>
[<a href="https://arxiv.org/abs/1909.02466">PDF</a>]
[<a href="https://github.com/zhangxiaosong18/FreeAnchor">Code</a>]
</td>
</tr>
<!-- #9 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ICCV-CMIDN.png" class="papericon"></td>
<td
class="pub_td2">Yan Gao, Boxiao Liu, Nan Guo, Xiaochun Ye, <u>Fang Wan</u>, Haihang You, and Dongrui Fan
<br><b>C-MIDN: Coupled Multiple Instance Detection Network with Segmentation Guidance forWeakly Supervised Object Detection</b>
<br>IEEE International Conference on Computer Vision (ICCV), 2019.
<br>
<!-- [<a href="">PDF</a>] -->
<!-- [<a href="">Code</a>] -->
</td>
</tr>
<!-- #8 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ICCV-DANet.png" class="papericon"></td>
<td
class="pub_td2">Haolan Xue, Chang Liu, <u>Fang Wan</u>, Jianbin Jiao, Qixiang Ye
<br><b>DANet: Divergent Activation for Weakly Supervised Object Localization</b>
<br>IEEE International Conference on Computer Vision (ICCV), 2019.
<br>
<!-- [<a href="">PDF</a>] -->
<!-- [<a href="">Code</a>] -->
</td>
</tr>
<!-- #7 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/PSG_CVPRW2019.jpg" class="papericon"></td>
<td
class="pub_td2">Chang Liu, Dezhao Luo, Yifei Zhang, Wei Ke, <u>Fang Wan</u> and Qixiang Ye
<br><b>Parametric Skeleton Generation via Gaussian Mixture Models</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), Long Beach, USA, 2019
<br>
[<a href="http://openaccess.thecvf.com/content_CVPRW_2019/papers/SkelNetOn/Liu_Parametric_Skeleton_Generation_via_Gaussian_Mixture_Models_CVPRW_2019_paper.pdf">PDF</a>]
</td>
</tr>
<!-- #6 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/MELM_PAMI.jpg" class="papericon"></td>
<td
class="pub_td2"><u>Fang Wan</u>, Pengxu Wei, Jianbin Jiao, Zhenjun Han and Qixiang Ye
<br><b>Min-Entropy Latent Model for Weakly Supervised Object Detection</b>
<br>IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
<br>
[<a href="https://arxiv.org/pdf/1902.06057.pdf">PDF</a>]
[<a href="https://github.com/Winfrand/MELM">Code</a>]
</td>
</tr>
<!-- #5 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/CMIL_CVPR.jpg" class="papericon"></td>
<td
class="pub_td2"><u>Fang Wan</u>, Chang Liu, Wei Ke, Xiangyang Ji, Jianbin Jiao and Qixiang Ye
<br><b>C-MIL: Continuation Multiple Instance Learning for Weakly Supervised Object Detection (Oral)</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019
<br>
[<a href="http://openaccess.thecvf.com/content_CVPR_2019/papers/Wan_C-MIL_Continuation_Multiple_Instance_Learning_for_Weakly_Supervised_Object_Detection_CVPR_2019_paper.pdf">PDF</a>]
[<a href="https://github.com/Winfrand/C-MIL">Code</a>]
</td>
</tr>
<!-- #4 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/ODN_CVPR.jpg" class="papericon"></td>
<td
class="pub_td2">Chang Liu, <u>Fang Wan</u>, Wei Ke, Zhuowei Xiao, Yuan Yao, Xiaosong Zhang, Qixiang Ye
<br><b>Orthogonal Decomposition Network for Pixel-wise Binary Classification</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019
<br>
[<a href="http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_Orthogonal_Decomposition_Network_for_Pixel-Wise_Binary_Classification_CVPR_2019_paper.pdf">PDF</a>]
[<a href="https://github.com/CV-PR/ODN">Code</a>]
</td>
</tr>
<!-- #3 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/SIXRay_CVPR.jpg" class="papericon"></td>
<td
class="pub_td2">Caijing Miao, Lingxi Xie, <u>Fang Wan</u>, Chi Su, Hongye Liu, Jianbin Jiao, Qixiang Ye
<br><b>SIXray: A Large-scale Security Inspection X-ray Benchmark for Prohibited Item Discovery in Overlapping Images</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019
<br>
[<a href="http://openaccess.thecvf.com/content_CVPR_2019/papers/Miao_SIXray_A_Large-Scale_Security_Inspection_X-Ray_Benchmark_for_Prohibited_Item_CVPR_2019_paper.pdf">PDF</a>]
[<a href="https://github.com/MeioJane/CHR">Code</a>]
[<a href="https://github.com/MeioJane/SIXray">Dataset</a>]
</td>
</tr>
<!-- #2 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/MELM_CVPR.jpg" class="papericon"></td>
<td
class="pub_td2"><u>Fang Wan</u>, Pengxu Wei, Jianbin Jiao, Zhenjun Han and Qixiang Ye
<br><b>Min-Entropy Latent Model for Weakly Supervised Object Detection</b>
<br>IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, 2018
<br>
[<a href="http://openaccess.thecvf.com/content_cvpr_2018/papers/Wan_Min-Entropy_Latent_Model_CVPR_2018_paper.pdf">PDF</a>]
[<a href="https://github.com/Winfrand/MELM">Code</a>]
</td>
</tr>
<!-- #1 -->
<tr>
<td class="pub_td1"><img src="WanFang_files/PaperFig/CTV_TIP.jpg" class="papericon"></td>
<td
class="pub_td2"> Pengxu Wei, Fei Qin, <u>Fang Wan</u>, Yi Zhu, Jianbin Jiao, Qixiang Ye
<br><b>Correlated Topic Vector for Scene Classification</b>
<br>IEEE Transactions on Image Processing (TIP), 2017
<br>
[<a href="https://ucassdl.cn/downloads/publication/TIP2017_WeiPengXu.pdf">PDF</a>]
</td>
</tr>
</tbody>
</table>
<br>
<H2>Awards</H2>
<LI> First Prize of Natural Science, The Chinese Institute of Electronics, 2022 </LI>
<LI> CAS Top 100 Doctoral Thesis, 2020 </LI>
<LI> CAS Special Research Assistant, 2019 </LI>
<LI> CAS Presidential Scholarship, 2019 </LI>
<LI> Initiative Postdocs Supporting Program, 2019 </LI>
<LI> Excellent Student Scholarship, Chinese Academy of Sciences, 2019. </LI>
<LI> First Place Prize of Aerial Vechle Detection Competition organized by Chinese Academy of Sciences, 2017. </LI>
<LI> Second Place Prize of Aerial Plane Detection Competition organized by Chinese Academy of Sciences, 2017. </LI>
<LI> Excellent Student Scholarship, Chinese Academy of Sciences, 2016. </LI>
<br> <br>
<H2>Statistics</H2>
<script type="text/javascript" src="//rf.revolvermaps.com/0/0/4.js?i=54mx2juv9fc&m=0&h=154&c=ff0000&r=10" async="async"></script>
</BODY>
</HTML>