25 citations · 46 across the 12 of their papers we have counts for
12 papers
Learning to Look Around: Enhancing Teleoperation and Learning with a Human-like Actuated Neck
Bipasha Sen, Michelle Wang, Nandini Thakur +2
We introduce a teleoperation system that integrates a 5 DOF actuated neck, designed to replicate natural human head movements and perception. By enabling behaviors like peeking or…
SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation
Aditya Agarwal, Gaurav Singh, Bipasha Sen +2
Careful robot manipulation in every-day cluttered environments requires an accurate understanding of the 3D scene, in order to grasp and place objects stably and reliably and to av…
Constrained 6-DoF Grasp Generation on Complex Shapes for Improved Dual-Arm Manipulation
Gaurav Singh, Sanket Kalwar, Md Faizal Karim +4
Efficiently generating grasp poses tailored to specific regions of an object is vital for various robotic manipulation tasks, especially in a dual-arm setup. This scenario presents…
ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning
Qiao Gu, Alihusein Kuwajerwala, Sacha Morin +13
For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and pla…
EDMP: Ensemble-of-costs-guided Diffusion for Motion Planning
Kallol Saha, Vishal Mandadi, Jayaram Reddy +5
Classical motion planning for robotic manipulation includes a set of general algorithms that aim to minimize a scene-specific cost of executing a given plan. This approach offers r…
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
Bipasha Sen, Gaurav Singh, Aditya Agarwal +3
Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects. However, learning generalizable…
SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping
Bipasha Sen, Aditya Agarwal, Gaurav Singh +3
Recovering full 3D shapes from partial observations is a challenging task that has been extensively addressed in the computer vision community. Many deep learning methods tackle th…
INR-V: A Continuous Representation Space for Video-based Generative Tasks
Bipasha Sen, Aditya Agarwal, Vinay P Namboodiri +1
Generating videos is a complex task that is accomplished by generating a set of temporally coherent images frame-by-frame. This limits the expressivity of videos to only image-base…
Towards MOOCs for Lipreading: Using Synthetic Talking Heads to Train Humans in Lipreading at Scale
Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay +2
Many people with some form of hearing loss consider lipreading as their primary mode of day-to-day communication. However, finding resources to learn or improve one's lipreading sk…
FaceOff: A Video-to-Video Face Swapping System
Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay +2
Doubles play an indispensable role in the movie industry. They take the place of the actors in dangerous stunt scenes or scenes where the same actor plays multiple characters. The…
Approaches and Challenges in Robotic Perception for Table-top Rearrangement and Planning
Aditya Agarwal, Bipasha Sen, Shankara Narayanan +3
Table-top Rearrangement and Planning is a challenging problem that relies heavily on an excellent perception stack. The perception stack involves observing and registering the 3D s…
Personalized One-Shot Lipreading for an ALS Patient
Bipasha Sen, Aditya Agarwal, Rudrabha Mukhopadhyay +2
Lipreading or visually recognizing speech from the mouth movements of a speaker is a challenging and mentally taxing task. Unfortunately, multiple medical conditions force people t…