6 citations · 11 across the 6 of their papers we have counts for
6 papers
CRC-RL: A Novel Visual Feature Representation Architecture for Unsupervised Reinforcement Learning
Darshita Jain, Anima Majumder, Samrat Dutta +1
This paper addresses the problem of visual feature representation learning with an aim to improve the performance of end-to-end reinforcement learning (RL) models. Specifically, a…
A Method for Handling Multi-class Imbalanced Data by Geometry based Information Sampling and Class Prioritized Synthetic Data Generation (GICaPS)
Anima Majumder, Samrat Dutta, Swagat Kumar +1
This paper looks into the problem of handling imbalanced data in a multi-label classification problem. The problem is solved by proposing two novel methods that primarily exploit t…
Unsupervised Monocular Depth Estimation for Night-time Images using Adversarial Domain Feature Adaptation
Madhu Vankadari, Sourav Garg, Anima Majumder +2
In this paper, we look into the problem of estimating per-pixel depth maps from unconstrained RGB monocular night-time images which is a difficult task that has not been addressed…
UnDEMoN 2.0: Improved Depth and Ego Motion Estimation through Deep Image Sampling
Madhu Babu, Swagat Kumar, Anima Majumder +1
In this paper, we provide an improved version of UnDEMoN model for depth and ego motion estimation from monocular images. The improvement is achieved by combining the standard bi-l…
A Deeper Insight into the UnDEMoN: Unsupervised Deep Network for Depth and Ego-Motion Estimation
Madhu Babu, Anima Majumder, Kaushik Das +1
This paper presents an unsupervised deep learning framework called UnDEMoN for estimating dense depth map and 6-DoF camera pose information directly from monocular images. The prop…
Design and Development of an automated Robotic Pick & Stow System for an e-Commerce Warehouse
Swagat Kumar, Anima Majumder, Samrat Dutta +9
In this paper, we provide details of a robotic system that can automate the task of picking and stowing objects from and to a rack in an e-commerce fulfillment warehouse. The syste…