5 citations · 7 across the 6 of their papers we have counts for
6 papers
MUSTAN: Multi-scale Temporal Context as Attention for Robust Video Foreground Segmentation
Praveen Kumar Pokala, Jaya Sai Kiran Patibandla, Naveen Kumar Pandey +1
Video foreground segmentation (VFS) is an important computer vision task wherein one aims to segment the objects under motion from the background. Most of the current methods are i…
AQUALLM: Audio Question Answering Data Generation Using Large Language Models
Swarup Ranjan Behera, Krishna Mohan Injeti, Jaya Sai Kiran Patibandla +2
Audio Question Answering (AQA) constitutes a pivotal task in which machines analyze both audio signals and natural language questions to produce precise natural language answers. T…
Learning Generative Prior with Latent Space Sparsity Constraints
Vinayak Killedar, Praveen Kumar Pokala, Chandra Sekhar Seelamantula
We address the problem of compressed sensing using a deep generative prior model and consider both linear and learned nonlinear sensing mechanisms, where the nonlinear one involves…
Quantized Proximal Averaging Network for Analysis Sparse Coding
Kartheek Kumar Reddy Nareddy, Mani Madhoolika Bulusu, Praveen Kumar Pokala +1
We solve the analysis sparse coding problem considering a combination of convex and non-convex sparsity promoting penalties. The multi-penalty formulation results in an iterative a…
NuSPAN: A Proximal Average Network for Nonuniform Sparse Model -- Application to Seismic Reflectivity Inversion
Swapnil Mache, Praveen Kumar Pokala, Kusala Rajendran +1
We solve the problem of sparse signal deconvolution in the context of seismic reflectivity inversion, which pertains to high-resolution recovery of the subsurface reflection coeffi…
DuRIN: A Deep-unfolded Sparse Seismic Reflectivity Inversion Network
Swapnil Mache, Praveen Kumar Pokala, Kusala Rajendran +1
We consider the reflection seismology problem of recovering the locations of interfaces and the amplitudes of reflection coefficients from seismic data, which are vital for estimat…