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Semi-supervised Counting via Pixel-by-pixel Density Distribution
  Modelling

Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling

23 February 2024
Hui Lin
Zhiheng Ma
Rongrong Ji
Yao Wang
Zhou Su
Xiaopeng Hong
Deyu Meng
ArXiv (abs)PDFHTMLGithub (4★)

Papers citing "Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling"

30 / 30 papers shown
Title
Boosting Crowd Counting via Multifaceted Attention
Boosting Crowd Counting via Multifaceted Attention
Hui Lin
Zhiheng Ma
Rongrong Ji
Yaowei Wang
Xiaopeng Hong
71
149
0
05 Mar 2022
Why the 1-Wasserstein distance is the area between the two marginal CDFs
Why the 1-Wasserstein distance is the area between the two marginal CDFs
M. Angelis
Ander Gray
81
14
0
05 Nov 2021
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Spatial Uncertainty-Aware Semi-Supervised Crowd Counting
Y. Meng
Hongrun Zhang
Yitian Zhao
Xiaoyun Yang
Xuesheng Qian
Xiaowei Huang
Yalin Zheng
OT
63
90
0
28 Jul 2021
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Per-Pixel Classification is Not All You Need for Semantic Segmentation
Bowen Cheng
Alex Schwing
Alexander Kirillov
VLMViT
210
1,548
0
13 Jul 2021
Segmenter: Transformer for Semantic Segmentation
Segmenter: Transformer for Semantic Segmentation
Robin Strudel
Ricardo Garcia Pinel
Ivan Laptev
Cordelia Schmid
ViT
215
1,470
0
12 May 2021
Transformer Tracking
Transformer Tracking
Xin Chen
Bin Yan
Jiawen Zhu
Dong Wang
Xiaoyun Yang
Huchuan Lu
ViT
69
960
0
29 Mar 2021
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective
  with Transformers
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Sixiao Zheng
Jiachen Lu
Hengshuang Zhao
Xiatian Zhu
Zekun Luo
...
Yanwei Fu
Jianfeng Feng
Tao Xiang
Philip Torr
Li Zhang
ViT
194
2,908
0
31 Dec 2020
TransTrack: Multiple Object Tracking with Transformer
TransTrack: Multiple Object Tracking with Transformer
Pei Sun
Jinkun Cao
Yi Jiang
Rufeng Zhang
Enze Xie
Zehuan Yuan
Changhu Wang
Ping Luo
ViTVOT
312
583
0
31 Dec 2020
End-to-End Video Instance Segmentation with Transformers
End-to-End Video Instance Segmentation with Transformers
Yuqing Wang
Zhaoliang Xu
Xinlong Wang
Chunhua Shen
Baoshan Cheng
Hao Shen
Huaxia Xia
ViT
82
691
0
30 Nov 2020
End-to-End Object Detection with Adaptive Clustering Transformer
End-to-End Object Detection with Adaptive Clustering Transformer
Minghang Zheng
Peng Gao
Renrui Zhang
Kunchang Li
Xiaogang Wang
Hongsheng Li
Hao Dong
ViT
154
199
0
18 Nov 2020
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Deformable DETR: Deformable Transformers for End-to-End Object Detection
Xizhou Zhu
Weijie Su
Lewei Lu
Bin Li
Xiaogang Wang
Jifeng Dai
ViT
234
5,091
0
08 Oct 2020
Distribution Matching for Crowd Counting
Distribution Matching for Crowd Counting
Boyu Wang
Huidong Liu
Dimitris Samaras
Minh Hoai
OT
74
288
0
28 Sep 2020
Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks
Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks
Yan Liu
Lingqiao Liu
Peng Wang
Pingping Zhang
Yinjie Lei
SSL
47
77
0
07 Jul 2020
End-to-End Object Detection with Transformers
End-to-End Object Detection with Transformers
Nicolas Carion
Francisco Massa
Gabriel Synnaeve
Nicolas Usunier
Alexander Kirillov
Sergey Zagoruyko
ViT3DVPINN
421
13,048
0
26 May 2020
Adaptive Mixture Regression Network with Local Counting Map for Crowd
  Counting
Adaptive Mixture Regression Network with Local Counting Map for Crowd Counting
Xiyang Liu
Jie Yang
Wenrui Ding
62
113
0
12 May 2020
JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method
JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method
Vishwanath A. Sindagi
R. Yasarla
Vishal M. Patel
73
227
0
07 Apr 2020
Towards Using Count-level Weak Supervision for Crowd Counting
Towards Using Count-level Weak Supervision for Crowd Counting
Yinjie Lei
Yan Liu
Pingping Zhang
Lingqiao Liu
67
97
0
29 Feb 2020
Focus on Semantic Consistency for Cross-domain Crowd Understanding
Focus on Semantic Consistency for Cross-domain Crowd Understanding
Tao Han
Junyu Gao
Yuan. Yuan
Qi. Wang
54
47
0
20 Feb 2020
NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization
NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization
Qi. Wang
Junyu Gao
Wei Lin
Xuelong Li
100
390
0
10 Jan 2020
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting
Vishwanath A. Sindagi
Vishal M. Patel
71
176
0
28 Aug 2019
From Open Set to Closed Set: Counting Objects by Spatial
  Divide-and-Conquer
From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
Haipeng Xiong
Hao Lu
Chengxin Liu
Liang Liu
Zhiguo Cao
Chunhua Shen
64
167
0
15 Aug 2019
Bayesian Loss for Crowd Count Estimation with Point Supervision
Bayesian Loss for Crowd Count Estimation with Point Supervision
Zhiheng Ma
Xing Wei
Xiaopeng Hong
Yihong Gong
3DPC
130
493
0
10 Aug 2019
Point in, Box out: Beyond Counting Persons in Crowds
Point in, Box out: Beyond Counting Persons in Crowds
Yuting Liu
Miaojing Shi
Qijun Zhao
Xiaofang Wang
3DPC
61
192
0
02 Apr 2019
Learning from Synthetic Data for Crowd Counting in the Wild
Learning from Synthetic Data for Crowd Counting in the Wild
Qi. Wang
Junyu Gao
Wei Lin
Yuan. Yuan
87
530
0
08 Mar 2019
Composition Loss for Counting, Density Map Estimation and Localization
  in Dense Crowds
Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds
Haroon Idrees
Muhmmad Tayyab
Kishan Athrey
Dong Zhang
S. Al-Maadeed
Nasir M. Rajpoot
M. Shah
80
680
0
02 Aug 2018
CrowdHuman: A Benchmark for Detecting Human in a Crowd
CrowdHuman: A Benchmark for Detecting Human in a Crowd
Shuai Shao
Zijian Zhao
Boxun Li
Tete Xiao
Gang Yu
Xiangyu Zhang
Jian Sun
281
687
0
30 Apr 2018
Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative
  Model
Sliced-Wasserstein Autoencoder: An Embarrassingly Simple Generative Model
Soheil Kolouri
Phillip E. Pope
Charles E. Martin
Gustavo K. Rohde
36
94
0
05 Apr 2018
CSRNet: Dilated Convolutional Neural Networks for Understanding the
  Highly Congested Scenes
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Yuhong Li
Xiaofan Zhang
Deming Chen
140
1,340
0
27 Feb 2018
DecideNet: Counting Varying Density Crowds Through Attention Guided
  Detection and Density Estimation
DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation
Jiang-Dong Liu
Chenqiang Gao
Deyu Meng
Alexander G. Hauptmann
59
347
0
18 Dec 2017
Switching Convolutional Neural Network for Crowd Counting
Switching Convolutional Neural Network for Crowd Counting
Deepak Babu Sam
Shiv Surya
R. Venkatesh Babu
88
889
0
01 Aug 2017
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