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Shubham Agrawal

7 accepted papers

2024

Deep Learning Based Named Entity Recognition Models for Recipes

COLING 2024main

Food touches our lives through various endeavors, including flavor, nourishment, health, and sustainability. Recipes are cultural capsules transmitted across generations via unstructured text. Automated protocols for recognizing named entities, the building blocks of recipe text, are of immense valu…

Cited by 11SourcePDFScholar
2024

RIC: Rotate-Inpaint-Complete for Generalizable Scene Reconstruction

ICRA 2024poster

General scene reconstruction refers to the task of estimating the full 3D geometry and texture of a scene containing previously unseen objects. In many practical applications such as AR/VR, autonomous navigation, and robotics, only a single view of the scene may be available, making the scene recons…

Cited by 2SourcecodeScholar
2023

Real-Time Simultaneous Multi-Object 3D Shape Reconstruction, 6DoF Pose Estimation and Dense Grasp Prediction

IROS 2023poster

In this paper, we present a realtime method for simultaneous object-level scene understanding and grasp prediction. Specifically, given a single RGBD image of a scene, our method localizes all the objects in the scene and for each object, it generates the following: full 3D shape, scale, pose with r…

Cited by 4SourceScholar
2022

Scene Editing as Teleoperation: A Case Study in 6DoF Kit Assembly

IROS 2022poster

Studies in robot teleoperation have been centered around action specifications-from continuous joint control to discrete end-effector pose control. However, these “robot-centric” interfaces often require skilled operators with extensive robotics expertise. To make teleoperation accessible to nonexpe…

Cited by 16SourcecodeScholar
2022

Simultaneous Object Reconstruction and Grasp Prediction using a Camera-centric Object Shell Representation

IROS 2022poster

Being able to grasp objects is a fundamental component of most robotic manipulation systems. In this paper, we present a new approach to simultaneously reconstruct a mesh and a dense grasp quality map of an object from a depth image. At the core of our approach is a novel camera-centric object repre…

Cited by 9SourceScholar
2021

AdaGrasp: Learning an Adaptive Gripper-Aware Grasping Policy

ICRA 2021poster

This paper aims to improve robots’ versatility and adaptability by allowing them to use a large variety of end- effector tools and quickly adapt to new tools. We propose AdaGrasp, a method to learn a single grasping policy that generalizes to novel grippers. By training on a large collection of grip…

Cited by 52SourcecodeScholar