9 citations · 10 across the 9 of their papers we have counts for
10 papers
Denoising data using convex relaxations
Charles Fefferman, Aalok Gangopadhyay, Matti Lassas +2
We study the problem of denoising observations \(Y_i=X_i+Z_i\), where the latent variables \(X_i\) are sampled from a low-dimensional manifold in \(\mathbb{R}^n\) and the noise var…
DMD-Net: Deep Mesh Denoising Network
Aalok Gangopadhyay, Shashikant Verma, Shanmuganathan Raman
We present Deep Mesh Denoising Network (DMD-Net), an end-to-end deep learning framework, for solving the mesh denoising problem. DMD-Net consists of a Graph Convolutional Neural Ne…
Hand Shadow Art: A Differentiable Rendering Perspective
Aalok Gangopadhyay, Prajwal Singh, Ashish Tiwari +1
Shadow art is an exciting form of sculptural art that produces captivating artistic effects through the 2D shadows cast by 3D shapes. Hand shadows, also known as shadow puppetry or…
On the randomized Horn problem and the surface tension of hives
Aalok Gangopadhyay, Hariharan Narayanan
Given two nonincreasing -tuples of real numbers , , the Horn problem asks for a description of all nonincreasing -tuples of real numbers such that there exist…
Flow Symmetrization for Parameterized Constrained Diffeomorphisms
Aalok Gangopadhyay, Dwip Dalal, Progyan Das +1
Diffeomorphisms play a crucial role while searching for shapes with fixed topological properties, allowing for smooth deformation of template shapes. Several approaches use diffeom…
Search Me Knot, Render Me Knot: Embedding Search and Differentiable Rendering of Knots in 3D
Aalok Gangopadhyay, Paras Gupta, Tarun Sharma +2
We introduce the problem of knot-based inverse perceptual art. Given multiple target images and their corresponding viewing configurations, the objective is to find a 3D knot-based…
A Graph Neural Network Approach for Temporal Mesh Blending and Correspondence
Aalok Gangopadhyay, Abhinav Narayan Harish, Prajwal Singh +1
We have proposed a self-supervised deep learning framework for solving the mesh blending problem in scenarios where the meshes are not in correspondence. To solve this problem, we…
APEX-Net: Automatic Plot Extractor Network
Aalok Gangopadhyay, Prajwal Singh, Shanmuganathan Raman
Automatic extraction of raw data from 2D line plot images is a problem of great importance having many real-world applications. Several algorithms have been proposed for solving th…
Deep Generative Filter for Motion Deblurring
Sainandan Ramakrishnan, Shubham Pachori. Aalok Gangopadhyay, Shanmuganathan Raman
Removing blur caused by camera shake in images has always been a challenging problem in computer vision literature due to its ill-posed nature. Motion blur caused due to the relati…
SA-CNN: Dynamic Scene Classification using Convolutional Neural Networks
Aalok Gangopadhyay, Shivam Mani Tripathi, Ishan Jindal +1
The task of classifying videos of natural dynamic scenes into appropriate classes has gained lot of attention in recent years. The problem especially becomes challenging when the c…