activity
20212024
most citedDTF-Net: Category-Level Pose Estimation and Shape Reconstruction via Deformable Template Field

6 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2024

Language-Conditioned Robotic Manipulation with Fast and Slow Thinking

Minjie Zhu, Yichen Zhu, Jinming Li +8

The language-conditioned robotic manipulation aims to transfer natural language instructions into executable actions, from simple pick-and-place to tasks requiring intent recogniti…

cs.RO2024

Object-Centric Instruction Augmentation for Robotic Manipulation

Junjie Wen, Yichen Zhu, Minjie Zhu +8

Humans interpret scenes by recognizing both the identities and positions of objects in their observations. For a robot to perform tasks such as \enquote{pick and place}, understand…

cs.RO2024

Visual Robotic Manipulation with Depth-Aware Pretraining

Wanying Wang, Jinming Li, Yichen Zhu +7

Recent work on visual representation learning has shown to be efficient for robotic manipulation tasks. However, most existing works pretrained the visual backbone solely on 2D ima…

cs.CV20236 cited

DTF-Net: Category-Level Pose Estimation and Shape Reconstruction via Deformable Template Field

Haowen Wang, Zhipeng Fan, Zhen Zhao +7

Estimating 6D poses and reconstructing 3D shapes of objects in open-world scenes from RGB-depth image pairs is challenging. Many existing methods rely on learning geometric feature…

cs.RO20231 cited

CMG-Net: An End-to-End Contact-Based Multi-Finger Dexterous Grasping Network

Mingze Wei, Yaomin Huang, Zhiyuan Xu +7

In this paper, we propose a novel representation for grasping using contacts between multi-finger robotic hands and objects to be manipulated. This representation significantly red…

cs.CV20233 cited

CP: Channel Pruning Plug-in for Point-based Networks

Yaomin Huang, Ning Liu, Zhengping Che +7

Channel pruning can effectively reduce both computational cost and memory footprint of the original network while keeping a comparable accuracy performance. Though great success ha…