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Grasp Generation

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Showing 1–50 of 52 papers

TitleStatusHype
Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered ScenesCode2
Diffusion-based Generation, Optimization, and Planning in 3D ScenesCode2
Grasping Field: Learning Implicit Representations for Human GraspsCode1
Splat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian SplattingCode1
UGG: Unified Generative GraspingCode1
6-DOF GraspNet: Variational Grasp Generation for Object ManipulationCode1
HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic ScenariosCode1
Toward a Plug-and-Play Vision-Based Grasping Module for RoboticsCode1
FFHNet : Generating Multi-Fingered Robotic Grasps for Unknown Objects in Real-timeCode1
ContactGen: Generative Contact Modeling for Grasp GenerationCode1
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered ScenesCode1
Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D inputCode1
OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object InteractionCode1
Orientation Attentive Robotic Grasp Synthesis with Augmented Grasp Map RepresentationCode1
PEGG-Net: Pixel-Wise Efficient Grasp Generation in Complex ScenesCode1
GRAB: A Dataset of Whole-Body Human Grasping of ObjectsCode1
CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from SimulationCode1
Decomposed Vector-Quantized Variational Autoencoder for Human Grasp GenerationCode1
KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D inputCode1
Multi-Modal Diffusion for Hand-Object Grasp GenerationCode0
A Unified Transformer-Based Framework with Pretraining For Whole Body Grasping Motion GenerationCode0
ClickDiff: Click to Induce Semantic Contact Map for Controllable Grasp Generation with Diffusion ModelsCode0
Bring Your Own Grasp Generator: Leveraging Robot Grasp Generation for Prosthetic GraspingCode0
Single-View Scene Point Cloud Human Grasp GenerationCode0
Exploiting Radiance Fields for Grasp Generation on Novel Synthetic Views—0
RegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation—0
SemGrasp: Semantic Grasp Generation via Language Aligned Discretization—0
Task-Oriented 6-DoF Grasp Pose Detection in Clutters—0
Reactive Human-to-Robot Handovers of Arbitrary Objects—0
Automatic generation of realistic training data for learning parallel-jaw grasping from synthetic stereo images—0
Beyond Top-Grasps Through Scene Completion—0
CoGrasp: 6-DoF Grasp Generation for Human-Robot Collaboration—0
Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation—0
Controllable Hand Grasp Generation for HOI and Efficient Evaluation Methods—0
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations—0
DexDiffuser: Generating Dexterous Grasps with Diffusion Models—0
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes—0
EvolvingGrasp: Evolutionary Grasp Generation via Efficient Preference Alignment—0
GAGrasp: Geometric Algebra Diffusion for Dexterous Grasping—0
GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation—0
GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation Demonstration and Imitation—0
GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training—0
Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation—0
Hand-Object Contact Consistency Reasoning for Human Grasps Generation—0
HUP-3D: A 3D multi-view synthetic dataset for assisted-egocentric hand-ultrasound pose estimation—0
Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering—0
Contact2Grasp: 3D Grasp Synthesis via Hand-Object Contact Constraint—0
Learning Precise Affordances from Egocentric Videos for Robotic Manipulation—0
Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances—0
Multi-fingered Robotic Hand Grasping in Cluttered Environments through Hand-object Contact Semantic Mapping—0
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