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Found 5 papers, 3 papers with code
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstruction
In our experiments, we apply our algorithm to reconstruct 3D objects in the ScanNet dataset and evaluate our results against CAD model retrieval-based reconstructions.
HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans
We present an automated and efficient approach for retrieving high-quality CAD models of objects and their poses in a scene captured by a moving RGB-D camera.
Automatically Annotating Indoor Images with CAD Models via RGB-D Scans
We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans.
Depth-aware Object Segmentation and Grasp Detection for Robotic Picking Tasks
In this paper, we present a novel deep neural network architecture for joint class-agnostic object segmentation and grasp detection for robotic picking tasks using a parallel-plate gripper.
End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB
In this work, we introduce a novel, end-to-end trainable CNN-based architecture to deliver high quality results for grasp detection suitable for a parallel-plate gripper, and semantic segmentation.
Ranked #1 on
Robotic Grasping
on Cornell Grasp Dataset
