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Chahat Deep Singh

10 accepted papers

2024

AcTExplore: Active Tactile Exploration on Unknown Objects

Amir-Hossein Shahidzadeh, Seong Jong Yoo, Pavan Mantripragada, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
ICRA 2024poster

Tactile exploration plays a crucial role in understanding object structures for fundamental robotics tasks such as grasping and manipulation. However, efficiently exploring such objects using tactile sensors is challenging, primarily due to the large-scale unknown environments and limited sensing co…

Cited by 5Source ↗Scholar ↗
2024

Active Human Pose Estimation via an Autonomous UAV Agent

Jingxi Chen, Botao He, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
IROS 2024poster

One of the core activities of an active observer involves moving to secure a "better" view of the scene, where the definition of "better" is task-dependent. This paper focuses on the task of human pose estimation from videos capturing a person’s activity. Self-occlusions within the scene can complic…

Cited by 2Source ↗Scholar ↗
2024

CodedEvents: Optimal Point-Spread-Function Engineering for 3D-Tracking with Event Cameras

Sachin Shah, Matthew A. Chan, Haoming Cai, Jingxi Chen, Sakshum Kulshrestha, Chahat Deep Singh +2
CVPR 2024poster

Point-spread-function (PSF) engineering is a well-established computational imaging technique that uses phase masks and other optical elements to embed extra information (e.g. depth) into the images captured by conventional CMOS image sensors. To date however PSF-engineering has not been applied to…

Cited by 2Source ↗PDF ↗Scholar ↗
2023

WorldGen: A Large Scale Generative Simulator

Chahat Deep Singh, Riya Kumari, Cornelia Fermüller, Nitin J. Sanket, Yiannis Aloimonos
ICRA 2023poster

In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various challenges such as scalability, cost efficiency and photorealism. To avoid expensive and strenuous dataset collection and annotations, rese…

Cited by 7Source ↗Scholar ↗
2021

0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera

Chethan M. Parameshwara, Nitin J. Sanket, Chahat Deep Singh, Cornelia Fermüller, Yiannis Aloimonos
ICRA 2021poster

Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks. Classical cameras suffer from motion blur in such scenarios rendering them effete. On the contrary, event cameras, because of their high temporal resolution and lack of motion blur, are tai…

Cited by 38Source ↗code ↗Scholar ↗
2021

EVPropNet: Detecting Drones By Finding Propellers For Mid-Air Landing And Following

Nitin J Sanket, Chahat Deep Singh, Chethan Parameshwara, Cornelia Fermüller, Guido de Croon, Yiannis Aloimonos
RSS 2021poster

The rapid rise of accessibility of unmanned aerial vehicles or drones pose a threat to general security and confidentiality. Most of the commercially available or custom-built drones are multi-rotors and are comprised of multiple propellers. Since these propellers rotate at a high-speed; they are ge…

Cited by 17Source ↗PDF ↗Scholar ↗
2021

MorphEyes: Variable Baseline Stereo For Quadrotor Navigation

Nitin J. Sanket, Chahat Deep Singh, Varun Asthana, Cornelia Fermüller, Yiannis Aloimonos
ICRA 2021poster

Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem of depth range being limited and dictated by the b…

Cited by 14Source ↗code ↗Scholar ↗
2021

NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction

Chahat Deep Singh, Nitin J. Sanket, Chethan M. Parameshwara, Cornelia Fermüller, Yiannis Aloimonos
IROS 2021poster

Recent advances in object segmentation have demonstrated that deep neural networks excel at object segmentation for specific classes in color and depth images. However, their performance is dictated by the number of classes and objects used for training, thereby hindering generalization to never see…

Cited by 5Source ↗Scholar ↗
2020

EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras

Nitin J. Sanket, Chethan M. Parameshwara, Chahat Deep Singh, Ashwin V. Kuruttukulam, Cornelia Fermüller, Davide Scaramuzza +1
ICRA 2020poster

Dynamic obstacle avoidance on quadrotors requires low latency. A class of sensors that are particularly suitable for such scenarios are event cameras. In this paper, we present a deep learning based solution for dodging multiple dynamic obstacles on a quadrotor with a single event camera and on-boar…

Cited by 96Source ↗code ↗Scholar ↗
2018

GapFlyt: Active Vision Based Minimalist Structure-Less Gap Detection For Quadrotor Flight

Nitin J. Sanket, Chahat Deep Singh, Kanishka Ganguly, Cornelia Fermüller, Yiannis Aloimonos
RA-L 2018

Although quadrotors, and aerial robots in general, are inherently active agents, their perceptual capabilities in literature so far have been mostly passive in nature. Researchers and practitioners today use traditional computer vision algorithms with the aim of building a representation of general

Cited by 88Source ↗code ↗Scholar ↗