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From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth
  Estimation of Dynamic Objects with Ground Contact Prior

From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth Estimation of Dynamic Objects with Ground Contact Prior

15 December 2023
Jaeho Moon
J. P. Bello
Byeongjun Kwon
Munchurl Kim
ArXivPDFHTML

Papers citing "From-Ground-To-Objects: Coarse-to-Fine Self-supervised Monocular Depth Estimation of Dynamic Objects with Ground Contact Prior"

16 / 16 papers shown
Title
Multi-Frame Self-Supervised Depth with Transformers
Multi-Frame Self-Supervised Depth with Transformers
Vitor Campagnolo Guizilini
Rares Andrei Ambrus
Di Chen
Sergey Zakharov
Adrien Gaidon
ViT
MDE
37
85
0
15 Apr 2022
Masked-attention Mask Transformer for Universal Image Segmentation
Masked-attention Mask Transformer for Universal Image Segmentation
Bowen Cheng
Ishan Misra
Alex Schwing
Alexander Kirillov
Rohit Girdhar
ISeg
188
2,315
0
02 Dec 2021
Attentive and Contrastive Learning for Joint Depth and Motion Field
  Estimation
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation
Seokju Lee
François Rameau
Fei Pan
In So Kweon
84
33
0
13 Oct 2021
Fine-grained Semantics-aware Representation Enhancement for
  Self-supervised Monocular Depth Estimation
Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation
Hyun-Joo Jung
Eunhyeok Park
S. Yoo
MDE
50
109
0
19 Aug 2021
Vision Transformers for Dense Prediction
Vision Transformers for Dense Prediction
René Ranftl
Alexey Bochkovskiy
V. Koltun
ViT
MDE
117
1,696
0
24 Mar 2021
Unsupervised Monocular Depth Learning in Dynamic Scenes
Unsupervised Monocular Depth Learning in Dynamic Scenes
Hanhan Li
A. Gordon
Hang Zhao
Vincent Casser
Angelova
MDE
92
135
0
30 Oct 2020
Forget About the LiDAR: Self-Supervised Depth Estimators with MED
  Probability Volumes
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes
Juan Luis Gonzalez
Munchurl Kim
143
86
0
09 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
SSL
MDE
60
232
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 Guidance
Marvin Klingner
Jan-Aike Termöhlen
Jonas Mikolajczyk
Tim Fingscheidt
MDE
104
320
0
14 Jul 2020
Self-supervised Monocular Trained Depth Estimation using Self-attention
  and Discrete Disparity Volume
Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volume
A. Johnston
G. Carneiro
MDE
52
233
0
31 Mar 2020
Self-supervised Learning with Geometric Constraints in Monocular Video:
  Connecting Flow, Depth, and Camera
Self-supervised Learning with Geometric Constraints in Monocular Video: Connecting Flow, Depth, and Camera
Yuhua Chen
Cordelia Schmid
C. Sminchisescu
SSL
MDE
52
244
0
12 Jul 2019
3D Packing for Self-Supervised Monocular Depth Estimation
3D Packing for Self-Supervised Monocular Depth Estimation
Vitor Campagnolo Guizilini
Rares Andrei Ambrus
Sudeep Pillai
Allan Raventos
Adrien Gaidon
SSL
3DPC
MDE
64
643
0
06 May 2019
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry
  with Deep Feature Reconstruction
Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction
Huangying Zhan
Ravi Garg
C. Weerasekera
Kejie Li
Harsh Agarwal
Ian Reid
MDE
48
631
0
11 Mar 2018
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
779
11,540
0
06 Apr 2016
Spatial Transformer Networks
Spatial Transformer Networks
Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
280
7,361
0
05 Jun 2015
Predicting Depth, Surface Normals and Semantic Labels with a Common
  Multi-Scale Convolutional Architecture
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
David Eigen
Rob Fergus
VLM
MDE
160
2,674
0
18 Nov 2014
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