activity
20212025
most citedGraph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects

2 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2025

Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation

Haofei Lu, Yifei Dong, Zehang Weng +3

We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial De…

cs.CV2024

Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images

Ci Li, Yi Yang, Zehang Weng +3

In recent years, 3D parametric animal models have been developed to aid in estimating 3D shape and pose from images and video. While progress has been made for humans, it's more ch…

cs.RO2024

Interactive Perception for Deformable Object Manipulation

Zehang Weng, Peng Zhou, Hang Yin +4

Interactive perception enables robots to manipulate the environment and objects to bring them into states that benefit the perception process. Deformable objects pose challenges to…

cs.RO2024

DexDiffuser: Generating Dexterous Grasps with Diffusion Models

Zehang Weng, Haofei Lu, Danica Kragic +1

We introduce DexDiffuser, a novel dexterous grasping method that generates, evaluates, and refines grasps on partial object point clouds. DexDiffuser includes the conditional diffu…

cs.RO2023

CAPGrasp: An Continuous Approach-Constrained Generative Grasp Sampler

Zehang Weng, Haofei Lu, Jens Lundell +1

We propose CAPGrasp, an 6-DoF continuous approach-constrained generative grasp sampler. It includes a novel learning strategy for trai…

cs.RO2023

GoNet: An Approach-Constrained Generative Grasp Sampling Network

Zehang Weng, Haofei Lu, Jens Lundell +1

This work addresses the problem of learning approach-constrained data-driven grasp samplers. To this end, we propose GoNet: a generative grasp sampler that can constrain the grasp…

cs.RO2021★ 2 cited

Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects

Zehang Weng, Fabian Paus, Anastasiia Varava +3

Capturing scene dynamics and predicting the future scene state is challenging but essential for robotic manipulation tasks, especially when the scene contains both rigid and deform…