Concepedia

Dense Grasp Detection

Dense Grasp Detection is a grasp detection framework that generates a dense, pixel-wise map of feasible grasp poses across an entire visual input, distinguishing itself from sparse methods by predicting multiple, spatially overlapping grasp configurations in contrast to isolated, discrete grasp proposals.

14

Publications

621

Citations

46

Authors

17

Institutions

Publications per year

2017–2026

12

Parents

Publications

14

GraspNet: An Efficient Convolutional Neural Network for Real-time Grasp Detection for Low-powered Devices

Umar Asif, Jianbin Tang, Stefan Harrer · 2018 · 167 citations · Full text

, , +17

A Vision-Based Robot Grasping System

Hu Cheng, Yingying Wang, Max Q.‐H. Meng · IEEE Sensors Journal · 2022 · 60 citations

, , +16

High precision grasp pose detection in dense clutter

Marcus Gualtieri, Andreas ten Pas, Kate Saenko et al. · 2016 · 57 citations · Full text

, , +17

S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes

Yuzhe Qin, Rui Chen, Hao Zhu et al. · arXiv (Cornell University) · 2019 · 55 citations · Full text

, , +17

Lightweight Pixel-Wise Generative Robot Grasping Detection Based on RGB-D Dense Fusion

Hongkun Tian, Kechen Song, Song Li et al. · IEEE Transactions on Instrumentation and Measurement · 2022 · 46 citations

, , +16

1–5 of 14

Authors

46

  1. HS
    Hao Su

    University of California San Diego, United States

    2 publications · 76 citations

    2

    h-index

  2. RW
    Robert W. Platt

    McGill University, Canada

    2 publications · 102 citations

    2

    h-index

  3. HC
    Hu Cheng

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 76 citations

    2

    h-index

  4. SH
    Stefan Harrer

    IBM Research - Australia, Australia

    2 publications · 212 citations

    2

    h-index

  5. JT
    Jianbin Tang

    IBM Research - Australia, Australia

    2 publications · 212 citations

    2

    h-index

1–5 of 46

Institutions

17

  1. University of Chinese Academy of Sciences

    Beijing, China

    2 h-index

    8 publications

    188 citations

  2. Chinese Academy of Sciences

    Beijing, China

    2 h-index

    13 publications

    314 citations

  3. Beijing Academy of Artificial Intelligence

    Beijing, China

    2 h-index

    8 publications

    188 citations

  4. Center for Excellence in Brain Science and Intelligence Technology

    Shanghai, China

    2 h-index

    2 publications

    47 citations

  5. Chinese University of Hong Kong, Shenzhen

    Shenzhen, China

    2 h-index

    2 publications

    75 citations

  6. Shandong Institute of Automation

    Jinan, China

    2 h-index

    13 publications

    314 citations

  7. Chinese University of Hong Kong

    Hong Kong, Hong Kong

    2 h-index

    6 publications

    228 citations

  8. Northeastern University

    Shenyang, China

    1 h-index

    5 publications

    230 citations

1–8 of 17

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 121 citations

    3

    h-index

  2. 2022 International Conference on Robotics and Automation (ICRA)

    Conference · 1 publications · 15 citations

    1

    h-index

  3. 1

    h-index

  4. IEEE Sensors Journal

    1 publications · 60 citations

    1

    h-index

  5. Computers and Electronics in Agriculture

    1 publications · 26 citations

    1

    h-index

1–5