InSpaceType: Reconsider Space Type in Indoor Monocular Depth Estimation

InSpaceType: Reconsider Space Type in Indoor Monocular Depth Estimation

24 September 2023

Cho-Ying Wu

Chin-Cheng Hsu

Ulrich Neumann

Papers citing "InSpaceType: Reconsider Space Type in Indoor Monocular Depth Estimation"

7 / 7 papers shown

Title
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data Lihe Yang Bingyi Kang Zilong Huang Xiaogang Xu Jiashi Feng Hengshuang Zhao VLM 149 706 0 19 Jan 2024
Revealing the Dark Secrets of Masked Image Modeling Zhenda Xie Zigang Geng Jingcheng Hu Zheng-Wei Zhang Han Hu Yue Cao VLM 188 105 0 26 May 2022
Toward Practical Monocular Indoor Depth Estimation Cho-Ying Wu Jialiang Wang Michael Hall Ulrich Neumann Shuochen Su 3DV MDE 43 62 0 04 Dec 2021
PLNet: Plane and Line Priors for Unsupervised Indoor Depth Estimation Hualie Jiang Laiyan Ding Junjie Hu Rui Huang 3DPC SSL MDE 51 19 0 12 Oct 2021
Scene Completeness-Aware Lidar Depth Completion for Driving Scenario Cho-Ying Wu Ulrich Neumann 3DV 22 9 0 15 Mar 2020
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou Quan Cui Xiu-Shen Wei Zhao-Min Chen 250 782 0 05 Dec 2019
Deep Ordinal Regression Network for Monocular Depth Estimation Huan Fu Mingming Gong Chaohui Wang Kayhan Batmanghelich Dacheng Tao MDE 188 1,707 0 06 Jun 2018