activity
20172026
most citedVision-based Robotic Grasping From Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review

472 citations · 940 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2026

KAConvNet: Kolmogorov-Arnold Convolutional Networks for Vision Recognition

Zhaoxiang Liu, Zhicheng Ma, Kaikai Zhao +2

The Convolutional Neural Networks (CNNs) have been the dominant and effective approach for general computer vision tasks. Recently, Kolmogorov-Arnold neural networks (KANs), based…

cs.SD2022★ 4 cited

A Novel Speech-Driven Lip-Sync Model with CNN and LSTM

Xiaohong Li, Xiang Wang, Kai Wang +1

Generating synchronized and natural lip movement with speech is one of the most important tasks in creating realistic virtual characters. In this paper, we present a combined deep…

cs.RO2019★ 472 cited

Vision-based Robotic Grasping From Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review

Guoguang Du, Kai Wang, Shiguo Lian +1

This paper presents a comprehensive survey on vision-based robotic grasping. We conclude three key tasks during vision-based robotic grasping, which are object localization, object…

cs.CV2019★ 164 cited

Deep Learning Based Robot for Automatically Picking up Garbage on the Grass

Jinqiang Bai, Shiguo Lian, Zhaoxiang Liu +2

This paper presents a novel garbage pickup robot which operates on the grass. The robot is able to detect the garbage accurately and autonomously by using a deep neural network for…

cs.CV2019★ 129 cited

Virtual-Blind-Road Following Based Wearable Navigation Device for Blind People

Jinqiang Bai, Shiguo Lian, Zhaoxiang Liu +2

To help the blind people walk to the destination efficiently and safely in indoor environment, a novel wearable navigation device is presented in this paper. The locating, way-find…

cs.CV2019★ 6 cited

Synthetic Data Generation and Adaption for Object Detection in Smart Vending Machines

Kai Wang, Fuyuan Shi, Wenqi Wang +2

This paper presents an improved scheme for the generation and adaption of synthetic images for the training of deep Convolutional Neural Networks(CNNs) to perform the object detect…