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Deng-Ping Fan (范登平)
Deng-Ping Fan (范登平)
Bestätigte E-Mail-Adresse bei nankai.edu.cn - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
W Wang, E Xie, X Li, DP Fan*, K Song, D Liang, T Lu*, P Luo, L Shao
International Conference on Computer Vision (ICCV, Oral, 2023 WAICYOP Award), 2021
42912021
Structure-measure: A New Way to Evaluate Foreground Maps
DP Fan, MM Cheng*, Y Liu, T Li, A Borji
International Conference on Computer Vision (ICCV, Spotlight), 2017
17602017
PVT v2: Improved Baselines with Pyramid Vision Transformer
W Wang*, E Xie, X Li, DP Fan, K Song, D Liang, T Lu, P Luo, L Shao
Computational Visual Media (CVMJ, Honorable Mention Award) 8 (3), 415–424, 2022
14812022
Pranet: Parallel Reverse Attention Network for Polyp Segmentation
DP Fan, GP Ji, T Zhou, G Chen, H Fu*, J Shen*, L Shao
MICCAI (2024 YSPIA Shortlist, JDC2021 Most Influential Application Paper, Oral), 2020
13482020
Enhanced-alignment Measure for Binary Foreground Map Evaluation
DP Fan, C Gong, Y Cao, B Ren*, MM Cheng, A Borji
International Joint Conference on Artificial Intelligence (IJCAI, Oral), 2018
12962018
Inf-Net: Automatic Covid-19 Lung Infection Segmentation from CT Images
DP Fan, T Zhou, GP Ji, Y Zhou, G Chen*, H Fu*, J Shen*, L Shao
IEEE Transactions on Medical Imaging (TMI) 39 (8), 2626-2637, 2020
12172020
EGNet: Edge guidance network for salient object detection
JX Zhao, JJ Liu, DP Fan, Y Cao, J Yang, MM Cheng*
International Conference on Computer Vision (ICCV), 8779-8788, 2019
11942019
Camouflaged Object Detection
DP Fan, GP Ji, G Sun, MM Cheng, J Shen*, L Shao
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, Oral), 2020
6382020
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
DP Fan, Z Lin, Z Zhang, M Zhu, MM Cheng*
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 32 (5 …, 2021
6042021
Shifting More Attention to Video Salient Object Detection
DP Fan, W Wang, MM Cheng*, J Shen
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, Best Paper …, 2019
5332019
JCS: An Explainable COVID-19 Diagnosis System by Joint Classification and Segmentation
YH Wu, SH Gao, J Mei, J Xu, DP Fan, RG Zhang, MM Cheng*
IEEE Transactions on Image Processing (TIP) 30, 3113-3126, 2021
5192021
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection
JX Zhao, Y Cao, DP Fan, MM Cheng*, XY Li, L Zhang
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
4522019
Concealed Object Detection
DP Fan, GP Ji, MM Cheng*, L Shao
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI …, 2022
4482022
Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
B Dong, W Wang, DP Fan*, J Li, H Fu, L Shao
CAAI Artificial Intelligence Research (AIR) 2, 9150015, 2023
3972023
UC-Net: Uncertainty inspired RGB-D saliency detection via conditional variational autoencoders
J Zhang, DP Fan*, Y Dai, S Anwar, FS Saleh, T Zhang, N Barnes
IEEE Conference on Computer Vision and Pattern Recognition (CVPR, Best Paper …, 2020
3972020
Camouflaged Object Segmentation with Distraction Mining
H Mei, GP Ji, Z Wei, X Yang*, X Wei, DP Fan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
3922021
Simultaneously Localize, Segment and Rank the Camouflaged Objects
Y Lv, J Zhang, Y Dai*, A Li, B Liu, N Barnes, DP Fan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
376*2021
Salient objects in clutter: Bringing salient object detection to the foreground
DP Fan, MM Cheng, JJ Liu, SH Gao, Q Hou, A Borji
European Conference on Computer Vision (ECCV), 2018
3732018
BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network
DP Fan^, Y Zhai^, A Borji, J Yang*, L Shao
European Conference on Computer Vision (ECCV), 2020
3702020
JL-DCF: Joint learning and densely-cooperative fusion framework for RGB-D salient object detection
K Fu, DP Fan*, GP Ji, Q Zhao
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
3622020
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