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Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge
  Distillation for Unsupervised Monocular Depth Estimation
v1v2 (latest)

Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation

11 March 2019
Andrea Pilzer
Stéphane Lathuilière
Andrii Zadaianchuk
Elisa Ricci
    MDE
ArXiv (abs)PDFHTML

Papers citing "Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation"

26 / 76 papers shown
SF-UDA$^{3D}$: Source-Free Unsupervised Domain Adaptation for
  LiDAR-Based 3D Object Detection
SF-UDA3D^{3D}3D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object DetectionInternational Conference on 3D Vision (3DV), 2020
Cristiano Saltori
Stéphane Lathuilière
Andrii Zadaianchuk
Elisa Ricci
Fabio Galasso
3DPC
250
36
0
16 Oct 2020
Approaches, Challenges, and Applications for Deep Visual Odometry:
  Toward to Complicated and Emerging Areas
Approaches, Challenges, and Applications for Deep Visual Odometry: Toward to Complicated and Emerging AreasIEEE Transactions on Cognitive and Developmental Systems (TCDS), 2020
Ke Min Wang
Sai Ma
Junlan Chen
Fan Ren
293
95
0
06 Sep 2020
DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
DESC: Domain Adaptation for Depth Estimation via Semantic ConsistencyInternational Journal of Computer Vision (IJCV), 2020
Adrian Lopez-Rodriguez
K. Mikolajczyk
MDE
212
49
0
03 Sep 2020
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation
  Synergized with Semantic Segmentation for Autonomous Driving
SynDistNet: Self-Supervised Monocular Fisheye Camera Distance Estimation Synergized with Semantic Segmentation for Autonomous DrivingIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
V. Kumar
Marvin Klingner
S. Yogamani
Stefan Milz
Tim Fingscheidt
Patrick Mäder
MDE
335
85
0
10 Aug 2020
Forget About the LiDAR: Self-Supervised Depth Estimators with MED
  Probability Volumes
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesNeural Information Processing Systems (NeurIPS), 2020
Juan Luis Gonzalez
Munchurl Kim
419
95
0
09 Aug 2020
Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
Jogendra Nath Kundu
Ambareesh Revanur
Govind V Waghmare
R. Venkatesh
R. Venkatesh Babu
3DH
140
18
0
04 Aug 2020
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion
Feature-metric Loss for Self-supervised Learning of Depth and Egomotion
Chang Shu
Kun Yu
Zhixiang Duan
Kuiyuan Yang
SSLMDE
180
261
0
21 Jul 2020
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object
  Problem by Semantic Guidance
Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic GuidanceEuropean Conference on Computer Vision (ECCV), 2020
Marvin Klingner
Jan-Aike Termöhlen
Jonas Mikolajczyk
Tim Fingscheidt
MDE
383
371
0
14 Jul 2020
Continual Adaptation for Deep Stereo
Continual Adaptation for Deep StereoIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Matteo Poggi
A. Tonioni
Fabio Tosi
S. Mattoccia
Luigi Di Stefano
OOD
319
38
0
10 Jul 2020
MiniNet: An extremely lightweight convolutional neural network for
  real-time unsupervised monocular depth estimation
MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation
Jun Liu
Qing Li
Rui Cao
Wenming Tang
Guoping Qiu
MDE
175
41
0
27 Jun 2020
Knowledge Distillation: A Survey
Knowledge Distillation: A Survey
Jianping Gou
B. Yu
Stephen J. Maybank
Dacheng Tao
VLM
1.9K
3,720
0
09 Jun 2020
On the uncertainty of self-supervised monocular depth estimation
On the uncertainty of self-supervised monocular depth estimation
Matteo Poggi
Filippo Aleotti
Fabio Tosi
S. Mattoccia
UQCVMDE
259
301
0
13 May 2020
On the Synergies between Machine Learning and Binocular Stereo for Depth
  Estimation from Images: a Survey
On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey
Matteo Poggi
Fabio Tosi
Konstantinos Batsos
Philippos Mordohai
S. Mattoccia
3DVMDE
285
15
0
18 Apr 2020
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised
  Representation Learning
DeFeat-Net: General Monocular Depth via Simultaneous Unsupervised Representation LearningComputer Vision and Pattern Recognition (CVPR), 2020
Jaime Spencer
Richard Bowden
Simon Hadfield
MDESSL
313
110
0
30 Mar 2020
Monocular Depth Estimation Based On Deep Learning: An Overview
Monocular Depth Estimation Based On Deep Learning: An OverviewScience China Technological Sciences (Sci China Technol Sci), 2020
Chaoqiang Zhao
Qiyu Sun
Chongzhen Zhang
Yang Tang
Feng Qian
MDE
527
282
0
14 Mar 2020
Blurry Video Frame Interpolation
Blurry Video Frame InterpolationComputer Vision and Pattern Recognition (CVPR), 2020
Wang Shen
Wenbo Bao
Guangtao Zhai
Li Chen
Xiongkuo Min
Zhiyong Gao
210
100
0
27 Feb 2020
Perception and Navigation in Autonomous Systems in the Era of Learning:
  A Survey
Perception and Navigation in Autonomous Systems in the Era of Learning: A SurveyIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
Yang Tang
Chaoqiang Zhao
Jianrui Wang
Chongzhen Zhang
Qiyu Sun
Weixing Zheng
W. Du
Feng Qian
Jürgen Kurths
699
112
0
08 Jan 2020
Data-Free Adversarial Distillation
Data-Free Adversarial Distillation
Gongfan Fang
Mingli Song
Chengchao Shen
Xinchao Wang
Da Chen
Xiuming Zhang
270
164
0
23 Dec 2019
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion
Dreaming to Distill: Data-free Knowledge Transfer via DeepInversionComputer Vision and Pattern Recognition (CVPR), 2019
Hongxu Yin
Pavlo Molchanov
Zhizhong Li
J. Álvarez
Arun Mallya
Derek Hoiem
N. Jha
Jan Kautz
432
651
0
18 Dec 2019
Deep 3D Pan via adaptive "t-shaped" convolutions with global and local
  adaptive dilations
Deep 3D Pan via adaptive "t-shaped" convolutions with global and local adaptive dilations
J. P. Bello
Munchurl Kim
MDE
178
0
0
02 Oct 2019
Self-Supervised Learning of Depth and Motion Under Photometric
  Inconsistency
Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
Tianwei Shen
Lei Zhou
Zixin Luo
Yao Yao
Shiwei Li
Jiahui Zhang
Tian Fang
Long Quan
SSLMDE
123
12
0
19 Sep 2019
Progressive Fusion for Unsupervised Binocular Depth Estimation using
  Cycled Networks
Progressive Fusion for Unsupervised Binocular Depth Estimation using Cycled NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
Andrea Pilzer
Stéphane Lathuilière
Dan Xu
M. Puscas
Elisa Ricci
Andrii Zadaianchuk
MDE
137
26
0
17 Sep 2019
Structured Coupled Generative Adversarial Networks for Unsupervised
  Monocular Depth Estimation
Structured Coupled Generative Adversarial Networks for Unsupervised Monocular Depth EstimationInternational Conference on 3D Vision (3DV), 2019
M. Puscas
Dan Xu
Andrea Pilzer
Andrii Zadaianchuk
GANMDE
113
20
0
15 Aug 2019
Enhancing self-supervised monocular depth estimation with traditional
  visual odometry
Enhancing self-supervised monocular depth estimation with traditional visual odometryInternational Conference on 3D Vision (3DV), 2019
Lorenzo Andraghetti
Panteleimon Myriokefalitakis
Pier Luigi Dovesi
Belén Luque
Matteo Poggi
Alessandro Pieropan
S. Mattoccia
MDE
187
42
0
08 Aug 2019
A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation
A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation
Jaehoon Cho
Dongbo Min
Youngjung Kim
Kwanghoon Sohn
MDE3DV
250
58
0
23 Apr 2019
Learning monocular depth estimation infusing traditional stereo
  knowledge
Learning monocular depth estimation infusing traditional stereo knowledge
Fabio Tosi
Filippo Aleotti
Matteo Poggi
S. Mattoccia
MDE
141
230
0
08 Apr 2019
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