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LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR
v1v2 (latest)

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

Computer Vision and Image Understanding (CVIU), 2021
8 September 2021
Florent Bartoccioni
Éloi Zablocki
P. Pérez
Matthieu Cord
Alahari Karteek
    MDE
ArXiv (abs)PDFHTMLGithub

Papers citing "LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR"

9 / 9 papers shown
Training Self-Supervised Depth Completion Using Sparse Measurements and a Single Image
Training Self-Supervised Depth Completion Using Sparse Measurements and a Single Image
Rizhao Fan
Zhigen Li
Heping Li
Ning An
215
0
0
20 Jul 2025
Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active
  Sensor
Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active SensorEuropean Conference on Computer Vision (ECCV), 2024
Andrea Conti
Matteo Poggi
Valerio Cambareri
S. Mattoccia
MDE
389
4
0
12 Sep 2024
Gated Fields: Learning Scene Reconstruction from Gated Videos
Gated Fields: Learning Scene Reconstruction from Gated Videos
Andrea Ramazzina
Stefanie Walz
Pragyan Dahal
Mario Bijelic
Felix Heide
350
4
0
30 May 2024
DepthP+P: Metric Accurate Monocular Depth Estimation using Planar and
  Parallax
DepthP+P: Metric Accurate Monocular Depth Estimation using Planar and Parallax
Sadra Safadoust
Fatma Guney
MDE
216
0
0
05 Jan 2023
Robust and accurate depth estimation by fusing LiDAR and Stereo
Robust and accurate depth estimation by fusing LiDAR and StereoMeasurement science and technology (Meas. Sci. Technol.), 2022
Guangyao Xu
Junfeng Fan
En Li
Xiaoyu Long
Xuewei Cao
3DV3DPC
167
7
0
13 Jul 2022
Visual Attention-based Self-supervised Absolute Depth Estimation using
  Geometric Priors in Autonomous Driving
Visual Attention-based Self-supervised Absolute Depth Estimation using Geometric Priors in Autonomous DrivingIEEE Robotics and Automation Letters (RA-L), 2022
Jie Xiang
Yun Wang
Lifeng An
Haiyang Liu
Zijun Wang
Jian Liu
MDE
322
27
0
18 May 2022
Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via
  Cross-modal Distillation
Drive&Segment: Unsupervised Semantic Segmentation of Urban Scenes via Cross-modal DistillationEuropean Conference on Computer Vision (ECCV), 2022
Antonín Vobecký
David Hurych
Oriane Siméoni
Spyros Gidaris
Andrei Bursuc
Patrick Pérez
Josef Sivic
3DPC
314
29
0
21 Mar 2022
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and
  Sparse Sensor Data
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data
A. L. Rodríguez
Benjamin Busam
K. Mikolajczyk
378
50
0
03 Aug 2020
On the Benefit of Adversarial Training for Monocular Depth Estimation
On the Benefit of Adversarial Training for Monocular Depth EstimationComputer Vision and Image Understanding (CVIU), 2019
R. Groenendijk
Sezer Karaoglu
Theo Gevers
Thomas Mensink
GANMDE
371
29
0
29 Oct 2019
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