Concepedia

Supervised Depth Estimation

Supervised Depth Estimation is a depth estimation approach that belongs to the class of supervised learning methods, distinguished by its reliance on labeled training data consisting of image inputs and corresponding ground-truth depth maps to learn a mapping from visual inputs to dense depth predictions.

35

Publications

3.9K

Citations

122

Authors

47

Institutions

Publications per year

2017–2026

30

Parents

Publications

35

Learning Depth from Single Monocular Images

Ashutosh Saxena, Sung Heon Chung, Andrew Y. Ng · 2005 · 939 citations

, , +16

3-D Depth Reconstruction from a Single Still Image

Ashutosh Saxena, Sung Heon Chung, Andrew Y. Ng · International Journal of Computer Vision · 2007 · 622 citations · Full text

, , +16

High speed obstacle avoidance using monocular vision and reinforcement learning

Jeff Michels, Ashutosh Saxena, Andrew Y. Ng · 2005 · 398 citations

, , +17

Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation

Ning Zhang, Francesco Nex, George Vosselman et al. · 2023 · 333 citations · Full text

, , +15

MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer

Chaoqiang Zhao, Youmin Zhang, Matteo Poggi et al. · 2022 · 232 citations

, , +16

1–5 of 35

Authors

122

  1. AY
    Andrew Y. Ng

    Stanford University, United States

    4 publications · 2K citations

    4

    h-index

  2. MK
    Munchurl Kim

    Korea Advanced Institute of Science and Technology, South Korea

    4 publications · 97 citations

    4

    h-index

  3. AS
    Ashutosh Saxena

    Cornell University, United States

    4 publications · 2K citations

    4

    h-index

  4. IM
    Ilya Makarov

    National Research University Higher School of Economics, Russia

    3 publications · 92 citations

    3

    h-index

  5. SH
    Sung Heon Chung

    Stanford University, United States

    2 publications · 1.6K citations

    2

    h-index

1–5 of 122

Institutions

47

  1. Stanford University

    Stanford, United States

    4 h-index

    12 publications

    6.1K citations

  2. University of Hong Kong

    Pok Fu Lam, Hong Kong

    3 h-index

    6 publications

    143 citations

  3. Korea Advanced Institute of Science and Technology

    Daejeon, South Korea

    2 h-index

    4 publications

    124 citations

  4. Tsinghua University

    Beijing, China

    2 h-index

    5 publications

    102 citations

  5. National Research University Higher School of Economics

    Moscow, Russia

    2 h-index

    3 publications

    102 citations

  6. Institute for Infocomm Research

    Singapore, Singapore

    2 h-index

    2 publications

    60 citations

  7. MediaTek (China)

    Beijing, China

    1 h-index

    7 publications

    245 citations

  8. University of Science and Technology of China

    Hefei, China

    1 h-index

    1 publications

    209 citations

1–8 of 47

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 278 citations

    6

    h-index

  2. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 2 publications · 94 citations

    2

    h-index

  3. International Journal of Computer Vision

    1 publications · 622 citations

    1

    h-index

  4. 1

    h-index

  5. Neurocomputing

    1 publications · 15 citations

    1

    h-index

1–5