25 citations · 68 across the 23 of their papers we have counts for
24 papers
Hierarchical Semantic Regularization of Latent Spaces in StyleGANs
Tejan Karmali, Rishubh Parihar, Susmit Agrawal +4
Progress in GANs has enabled the generation of high-resolution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such images vi…
Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detection
Debottam Dutta, Debarpan Bhattacharya, Sriram Ganapathy +3
In this paper, we describe an approach for representation learning of audio signals for the task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D convo…
Svadhyaya system for the Second Diagnosing COVID-19 using Acoustics Challenge 2021
Deepak Mittal, Amir H. Poorjam, Debottam Dutta +4
This report describes the system used for detecting COVID-19 positives using three different acoustic modalities, namely speech, breathing, and cough in the second DiCOVA challenge…
Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features
Chieh Hubert Lin, Hsin-Ying Lee, Hung-Yu Tseng +2
Recent studies show that paddings in convolutional neural networks encode absolute position information which can negatively affect the model performance for certain tasks. However…
SISL:Self-Supervised Image Signature Learning for Splicing Detection and Localization
Susmit Agrawal, Prabhat Kumar, Siddharth Seth +3
Recent algorithms for image manipulation detection almost exclusively use deep network models. These approaches require either dense pixelwise groundtruth masks, camera ids, or ima…
Permutation Invariant Representations with Applications to Graph Deep Learning
Radu Balan, Naveed Haghani, Maneesh Singh
This paper presents primarily two Euclidean embeddings of the quotient space generated by matrices that are identified modulo arbitrary row permutations. The original application i…
VQ-Flows: Vector Quantized Local Normalizing Flows
Sahil Sidheekh, Chris B. Dock, Tushar Jain +2
Normalizing flows provide an elegant approach to generative modeling that allows for efficient sampling and exact density evaluation of unknown data distributions. However, current…
Class Incremental Online Streaming Learning
Soumya Banerjee, Vinay Kumar Verma, Toufiq Parag +2
A wide variety of methods have been developed to enable lifelong learning in conventional deep neural networks. However, to succeed, these methods require a `batch' of samples to b…
SpliceOut: A Simple and Efficient Audio Augmentation Method
Arjit Jain, Pranay Reddy Samala, Deepak Mittal +2
Time masking has become a de facto augmentation technique for speech and audio tasks, including automatic speech recognition (ASR) and audio classification, most notably as a part…
Attentive Contractive Flow with Lipschitz-constrained Self-Attention
Avideep Mukherjee, Badri Narayan Patro, Vinay P. Namboodiri
Normalizing flows provide an elegant method for obtaining tractable density estimates from distributions by using invertible transformations. The main challenge is to improve the e…
Is My Model Using The Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning
Vivek Gupta, Riyaz A. Bhat, Atreya Ghosal +3
Neural models command state-of-the-art performance across NLP tasks, including ones involving "reasoning". Models claiming to reason about the evidence presented to them should att…
Deep Implicit Surface Point Prediction Networks
Rahul Venkatesh, Tejan Karmali, Sarthak Sharma +4
Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit repr…
Learning to Stylize Novel Views
Hsin-Ping Huang, Hung-Yu Tseng, Saurabh Saini +2
We tackle a 3D scene stylization problem - generating stylized images of a scene from arbitrary novel views given a set of images of the same scene and a reference image of the des…
DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces
Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh +2
High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classic…
HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
Yichen Jiang, Shikha Bordia, Zheng Zhong +3
We introduce HoVer (HOppy VERification), a dataset for many-hop evidence extraction and fact verification. It challenges models to extract facts from several Wikipedia articles tha…
ProAlignNet : Unsupervised Learning for Progressively Aligning Noisy Contours
VSR Veeravasarapu, Abhishek Goel, Deepak Mittal +1
Contour shape alignment is a fundamental but challenging problem in computer vision, especially when the observations are partial, noisy, and largely misaligned. Recent ConvNet-bas…
End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition
Shaofei Wang, Vishnu Lokhande, Maneesh Singh +2
Modern computer vision (CV) is often based on convolutional neural networks (CNNs) that excel at hierarchical feature extraction. The previous generation of CV approaches was often…
Wavelets to the Rescue: Improving Sample Quality of Latent Variable Deep Generative Models
Prashnna K Gyawali, Rudra Saha, Linwei Wang +2
Variational Autoencoders (VAE) are probabilistic deep generative models underpinned by elegant theory, stable training processes, and meaningful manifold representations. However,…
Progressive Domain Adaptation for Object Detection
Han-Kai Hsu, Chun-Han Yao, Yi-Hsuan Tsai +4
Recent deep learning methods for object detection rely on a large amount of bounding box annotations. Collecting these annotations is laborious and costly, yet supervised models do…
Sampling Bias in Deep Active Classification: An Empirical Study
Ameya Prabhu, Charles Dognin, Maneesh Singh
The exploding cost and time needed for data labeling and model training are bottlenecks for training DNN models on large datasets. Identifying smaller representative data samples w…
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution
Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh +1
In this paper, we introduce a new optimization approach to Entity Resolution. Traditional approaches tackle entity resolution with hierarchical clustering, which does not benefit f…
To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics
Aurobrata Ghosh, Zheng Zhong, Steve Cruz +3
We consider an information theoretic approach to address the problem of identifying fake digital images. We propose an innovative method to formulate the issue of localizing manipu…
SpliceRadar: A Learned Method For Blind Image Forensics
Aurobrata Ghosh, Zheng Zhong, Terrance E Boult +1
Detection and localization of image manipulations like splices are gaining in importance with the easy accessibility of image editing softwares. While detection generates a verdict…
Diverse Image-to-Image Translation via Disentangled Representations
Hsin-Ying Lee, Hung-Yu Tseng, Jia-Bin Huang +2
Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for many applications: 1) the lack of aligned training pairs and 2) m…