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. 1801.04720
  4. Cited By
Combining Stereo Disparity and Optical Flow for Basic Scene Flow

Combining Stereo Disparity and Optical Flow for Basic Scene Flow

15 January 2018
René Schuster
C. Bailer
Oliver Wasenmüller
D. Stricker
    3DPC
ArXiv (abs)PDFHTML

Papers citing "Combining Stereo Disparity and Optical Flow for Basic Scene Flow"

15 / 15 papers shown
Title
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene
  Flow
MonoComb: A Sparse-to-Dense Combination Approach for Monocular Scene Flow
René Schuster
C. Unger
D. Stricker
MDE
28
3
0
21 Oct 2020
FC-DCNN: A densely connected neural network for stereo estimation
FC-DCNN: A densely connected neural network for stereo estimation
Dominik Hirner
Friedrich Fraundorfer
3DV3DPC
51
13
0
14 Oct 2020
Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection
  and Tracking
Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection and Tracking
Thomas Eppenberger
Gianluca Cesari
Marcin Dymczyk
Roland Siegwart
Renaud Dubé
176
43
0
21 Jul 2020
Self-Supervised Monocular Scene Flow Estimation
Self-Supervised Monocular Scene Flow Estimation
Junhwa Hur
Stefan Roth
3DPCMDE
61
102
0
08 Apr 2020
Holopix50k: A Large-Scale In-the-wild Stereo Image Dataset
Holopix50k: A Large-Scale In-the-wild Stereo Image Dataset
Yiwen Hua
Puneet Kohli
Pritish Uplavikar
Anand Ravi
Saravanan Gunaseelan
Jason Orozco
Edward Li
3DVMDE
129
43
0
25 Mar 2020
SENSE: a Shared Encoder Network for Scene-flow Estimation
SENSE: a Shared Encoder Network for Scene-flow Estimation
Huaizu Jiang
Deqing Sun
Varun Jampani
Zhaoyang Lv
Erik Learned-Miller
Jan Kautz
3DPCVOS
88
74
0
27 Oct 2019
Driving Datasets Literature Review
Driving Datasets Literature Review
Charles-Éric Noel Laflamme
Franccois Pomerleau
Philippe Giguère
66
19
0
26 Oct 2019
TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
Mostafa El-Khamy
Haoyu Ren
Xianzhi Du
Jungwon Lee
ViTMDE
61
1
0
11 Jun 2019
DeLiO: Decoupled LiDAR Odometry
DeLiO: Decoupled LiDAR Odometry
Queens Maria Thomas
Oliver Wasenmüller
D. Stricker
29
10
0
29 Apr 2019
SDC - Stacked Dilated Convolution: A Unified Descriptor Network for
  Dense Matching Tasks
SDC - Stacked Dilated Convolution: A Unified Descriptor Network for Dense Matching Tasks
René Schuster
Oliver Wasenmüller
C. Unger
D. Stricker
MDE
90
50
0
05 Apr 2019
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and
  Robust Interpolation for Scene Flow Estimation
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
René Schuster
Oliver Wasenmüller
C. Unger
G. Kuschk
D. Stricker
70
18
0
26 Feb 2019
Dense Scene Flow from Stereo Disparity and Optical Flow
Dense Scene Flow from Stereo Disparity and Optical Flow
René Schuster
Oliver Wasenmüller
D. Stricker
35
6
0
30 Aug 2018
Occlusions, Motion and Depth Boundaries with a Generic Network for
  Disparity, Optical Flow or Scene Flow Estimation
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation
Eddy Ilg
Tonmoy Saikia
Margret Keuper
Thomas Brox
3DPC
140
206
0
06 Aug 2018
SceneEDNet: A Deep Learning Approach for Scene Flow Estimation
SceneEDNet: A Deep Learning Approach for Scene Flow Estimation
Ravi Kumar Thakur
Snehasis Mukherjee
3DPC
51
6
0
10 Jul 2018
SceneFlowFields: Dense Interpolation of Sparse Scene Flow
  Correspondences
SceneFlowFields: Dense Interpolation of Sparse Scene Flow Correspondences
René Schuster
Oliver Wasenmüller
G. Kuschk
C. Bailer
D. Stricker
65
38
0
27 Oct 2017
1