Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects

15 March 2024

Papers citing "Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects"

6 / 6 papers shown

Title
Prompt-responsive Object Retrieval with Memory-augmented Student-Teacher Learning Malte Mosbach Sven Behnke 31 0 0 04 May 2025
Rethinking RGB-Event Semantic Segmentation with a Novel Bidirectional Motion-enhanced Event Representation Zhen Yao Xiaowen Ying Mooi Choo Choo Chuah 35 0 0 02 May 2025
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Cluttered Environments Lixin Xu Zixuan Liu Zhewei Gui Jingxiang Guo Zeyu Jiang Zhixuan Xu Chongkai Gao Lin Shao 32 0 0 06 Apr 2025
Grasp What You Want: Embodied Dexterous Grasping System Driven by Your Voice Junliang Li Kai Ye Haolan Kang Mingxuan Liang Yuhang Wu Zhenhua Liu Huiping Zhuang Rui Huang Yongquan Chen 78 0 0 14 Dec 2024
Grasping by Hanging: a Learning-Free Grasping Detection Method for Previously Unseen Objects Wanze Li Wan Su Gregory Chirikjian 32 0 0 13 Aug 2024
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,109 0 02 Dec 2016