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. 1703.04309
  4. Cited By
End-to-End Learning of Geometry and Context for Deep Stereo Regression

End-to-End Learning of Geometry and Context for Deep Stereo Regression

13 March 2017
Alex Kendall
H. Martirosyan
Saumitro Dasgupta
Peter Henry
Ryan Kennedy
Abraham Bachrach
Adam Bry
    3DV3DPCMDE
ArXiv (abs)PDFHTML

Papers citing "End-to-End Learning of Geometry and Context for Deep Stereo Regression"

27 / 27 papers shown
Title
A Wavelet-based Stereo Matching Framework for Solving Frequency Convergence Inconsistency
Xiaobao Wei
Jiawei Liu
Dongbo Yang
Junda Cheng
Changyong Shu
Wei Wang
3DV
63
0
0
23 May 2025
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang
Mingxiu Cai
Haoran Wang
Gaochang Wu
Tianyou Chai
Xiatian Zhu
99
0
0
02 May 2025
SC3EF: A Joint Self-Correlation and Cross-Correspondence Estimation Framework for Visible and Thermal Image Registration
SC3EF: A Joint Self-Correlation and Cross-Correspondence Estimation Framework for Visible and Thermal Image Registration
Xi Tong
Xing Luo
Jiangxin Yang
Yanpeng Cao
98
0
0
17 Apr 2025
Distilling Stereo Networks for Performant and Efficient Leaner Networks
Distilling Stereo Networks for Performant and Efficient Leaner Networks
Rafia Rahim
Samuel Woerz
A. Zell
175
0
0
24 Mar 2025
LeanStereo: A Leaner Backbone based Stereo Network
LeanStereo: A Leaner Backbone based Stereo Network
Rafia Rahim
Samuel Woerz
A. Zell
3DV
171
0
0
24 Mar 2025
RGB-Phase Speckle: Cross-Scene Stereo 3D Reconstruction via Wrapped Pre-Normalization
RGB-Phase Speckle: Cross-Scene Stereo 3D Reconstruction via Wrapped Pre-Normalization
Kai Yang
Zijian Bai
Yang Xiao
Xinyu Li
Xiaohan Shi
162
0
0
08 Mar 2025
Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer
Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer
Ziyang Chen
Yongjun Zhang
Wenting Li
Bingshu Wang
Yabo Wu
Yong Zhao
C. L. P. Chen
229
0
0
02 Jan 2025
Helvipad: A Real-World Dataset for Omnidirectional Stereo Depth Estimation
Helvipad: A Real-World Dataset for Omnidirectional Stereo Depth Estimation
Mehdi Zayene
Jannik Endres
Albias Havolli
Charles Corbière
Salim Cherkaoui
Alexandre Kontouli
Alexandre Alahi
MDE
251
1
0
27 Nov 2024
Robust and Flexible Omnidirectional Depth Estimation with Multiple 360-degree Cameras
Robust and Flexible Omnidirectional Depth Estimation with Multiple 360-degree Cameras
Ming Li
Xueqian Jin
Xuejiao Hu
Jinghao Cao
S. Du
Yang Li
MDE
139
0
0
23 Sep 2024
IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching
IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matching
Gangwei Xu
Xianqi Wang
Zhaoxing Zhang
Junda Cheng
Chunyuan Liao
Xin Yang
3DV
122
12
0
01 Sep 2024
LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation
LightStereo: Channel Boost Is All You Need for Efficient 2D Cost Aggregation
Xianda Guo
Chenming Zhang
Dujun Nie
Wenzhao Zheng
Youmin Zhang
Long Chen
Long Chen
73
7
0
28 Jun 2024
Monocular Depth Estimation Based On Deep Learning: An Overview
Monocular Depth Estimation Based On Deep Learning: An Overview
Chaoqiang Zhao
Qiyu Sun
Chongzhen Zhang
Yang Tang
Feng Qian
MDE
208
255
0
14 Mar 2020
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOSSSeg
747
37,895
0
20 May 2016
Unsupervised CNN for Single View Depth Estimation: Geometry to the
  Rescue
Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue
Ravi Garg
B. V. Kumar
G. Carneiro
Ian Reid
3DVMDE
121
1,530
0
16 Mar 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,510
0
10 Dec 2015
A Large Dataset to Train Convolutional Networks for Disparity, Optical
  Flow, and Scene Flow Estimation
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
N. Mayer
Eddy Ilg
Philip Häusser
Philipp Fischer
Daniel Cremers
Alexey Dosovitskiy
Thomas Brox
3DPC
69
2,648
0
07 Dec 2015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
1.1K
15,821
0
02 Nov 2015
Stereo Matching by Training a Convolutional Neural Network to Compare
  Image Patches
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
Jure Zbontar
Yann LeCun
3DV
152
1,389
0
20 Oct 2015
DeepStereo: Learning to Predict New Views from the World's Imagery
DeepStereo: Learning to Predict New Views from the World's Imagery
John Flynn
Ivan Neulander
James Philbin
Noah Snavely
3DV
120
652
0
22 Jun 2015
Learning to Compare Image Patches via Convolutional Neural Networks
Learning to Compare Image Patches via Convolutional Neural Networks
Sergey Zagoruyko
N. Komodakis
SSL
92
1,436
0
14 Apr 2015
Learning Depth from Single Monocular Images Using Deep Convolutional
  Neural Fields
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
Fayao Liu
Chunhua Shen
Guosheng Lin
Ian Reid
MDE
172
1,198
0
26 Feb 2015
Computing the Stereo Matching Cost with a Convolutional Neural Network
Computing the Stereo Matching Cost with a Convolutional Neural Network
Jure Zbontar
Yann LeCun
3DV
74
770
0
15 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
578
27,338
0
01 Sep 2014
Depth Map Prediction from a Single Image using a Multi-Scale Deep
  Network
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen
Christian Puhrsch
Rob Fergus
MDE3DPC3DV
241
4,066
0
09 Jun 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
314
7,317
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAttSSL
595
15,904
0
12 Nov 2013
Rich feature hierarchies for accurate object detection and semantic
  segmentation
Rich feature hierarchies for accurate object detection and semantic segmentation
Ross B. Girshick
Jeff Donahue
Trevor Darrell
Jitendra Malik
ObjD
291
26,223
0
11 Nov 2013
1