ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1803.09453
  4. Cited By
CNN in MRF: Video Object Segmentation via Inference in A CNN-Based
  Higher-Order Spatio-Temporal MRF

CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF

26 March 2018
Linchao Bao
Baoyuan Wu
Wen Liu
    VOS
ArXivPDFHTML

Papers citing "CNN in MRF: Video Object Segmentation via Inference in A CNN-Based Higher-Order Spatio-Temporal MRF"

21 / 21 papers shown
Title
Leveraging Motion Information for Better Self-Supervised Video Correspondence Learning
Leveraging Motion Information for Better Self-Supervised Video Correspondence Learning
Zihan Zhoua
Changrui Daia
Aibo Songa
Xiaolin Fang
VOS
85
0
0
15 Mar 2025
Learning Spatial-Semantic Features for Robust Video Object Segmentation
Learning Spatial-Semantic Features for Robust Video Object Segmentation
Xin Li
Deshui Miao
Zhenyu He
Yansen Wang
Huchuan Lu
Ming-Hsuan Yang
VOS
104
4
0
10 Jul 2024
DMM-Net: Differentiable Mask-Matching Network for Video Object
  Segmentation
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation
Fangyin Wei
Renjie Liao
Li Gu
Yuwen Xiong
Sanja Fidler
R. Urtasun
VOS
46
77
0
27 Sep 2019
MaskRNN: Instance Level Video Object Segmentation
MaskRNN: Instance Level Video Object Segmentation
Yuan-Ting Hu
Jia-Bin Huang
Alex Schwing
VOS
45
182
0
29 Mar 2018
SegFlow: Joint Learning for Video Object Segmentation and Optical Flow
SegFlow: Joint Learning for Video Object Segmentation and Optical Flow
Jingchun Cheng
Yi-Hsuan Tsai
Shengjin Wang
Ming-Hsuan Yang
VOS
41
415
0
20 Sep 2017
Pixel-Level Matching for Video Object Segmentation using Convolutional
  Neural Networks
Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks
Jae Shin Yoon
François Rameau
Junsik Kim
Seokju Lee
Seunghak Shin
In So Kweon
VOS
45
158
0
17 Aug 2017
Online Adaptation of Convolutional Neural Networks for Video Object
  Segmentation
Online Adaptation of Convolutional Neural Networks for Video Object Segmentation
P. Voigtlaender
Bastian Leibe
VOS
89
394
0
28 Jun 2017
The 2017 DAVIS Challenge on Video Object Segmentation
The 2017 DAVIS Challenge on Video Object Segmentation
Jordi Pont-Tuset
Federico Perazzi
Sergi Caelles
Pablo Arbeláez
A. Sorkine-Hornung
Luc Van Gool
VGen
VOS
49
1,193
0
03 Apr 2017
Super-Trajectory for Video Segmentation
Super-Trajectory for Video Segmentation
Wenguan Wang
Jianbing Shen
Jianwen Xie
Fatih Porikli
VOS
39
46
0
28 Feb 2017
Video Propagation Networks
Video Propagation Networks
Varun Jampani
Raghudeep Gadde
Peter V. Gehler
DiffM
36
230
0
16 Dec 2016
Learning Video Object Segmentation from Static Images
Learning Video Object Segmentation from Static Images
Anna Khoreva
Federico Perazzi
Rodrigo Benenson
Bernt Schiele
A. Sorkine-Hornung
VOS
43
585
0
08 Dec 2016
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Eddy Ilg
N. Mayer
Tonmoy Saikia
Margret Keuper
Alexey Dosovitskiy
Thomas Brox
3DPC
146
3,072
0
06 Dec 2016
One-Shot Video Object Segmentation
One-Shot Video Object Segmentation
Sergi Caelles
Kevis-Kokitsi Maninis
Jordi Pont-Tuset
Laura Leal-Taixé
Daniel Cremers
Luc Van Gool
VOS
53
909
0
16 Nov 2016
Deep Learning Markov Random Field for Semantic Segmentation
Deep Learning Markov Random Field for Semantic Segmentation
Ziwei Liu
Xiaoxiao Li
Ping Luo
Chen Change Loy
Xiaoou Tang
3DV
50
160
0
23 Jun 2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets,
  Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
144
18,136
0
02 Jun 2016
Higher Order Conditional Random Fields in Deep Neural Networks
Higher Order Conditional Random Fields in Deep Neural Networks
Anurag Arnab
Sadeep Jayasumana
Shuai Zheng
Philip Torr
SSeg
43
230
0
25 Nov 2015
Fully Connected Deep Structured Networks
Fully Connected Deep Structured Networks
Alex Schwing
R. Urtasun
SSeg
89
308
0
09 Mar 2015
Conditional Random Fields as Recurrent Neural Networks
Conditional Random Fields as Recurrent Neural Networks
Shuai Zheng
Sadeep Jayasumana
Bernardino Romera-Paredes
Vibhav Vineet
Zhizhong Su
Dalong Du
Chang Huang
Philip Torr
SSeg
128
2,533
0
11 Feb 2015
Robust Piecewise-Constant Smoothing: M-Smoother Revisited
Robust Piecewise-Constant Smoothing: M-Smoother Revisited
Linchao Bao
Qingxiong Yang
22
4
0
28 Oct 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
650
99,991
0
04 Sep 2014
Efficient Inference in Fully Connected CRFs with Gaussian Edge
  Potentials
Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials
Philipp Krahenbuhl
V. Koltun
65
3,445
0
20 Oct 2012
1