9 citations · 17 across the 3 of their papers we have counts for
6 papers
GAMA: Generative Adversarial Multi-Object Scene Attacks
Abhishek Aich, Calvin-Khang Ta, Akash Gupta +4
The majority of methods for crafting adversarial attacks have focused on scenes with a single dominant object (e.g., images from ImageNet). On the other hand, natural scenes includ…
Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image
Calvin-Khang Ta, Abhishek Aich, Akash Gupta +1
Image enhancement approaches often assume that the noise is signal independent, and approximate the degradation model as zero-mean additive Gaussian. However, this assumption does…
Deep Quantized Representation for Enhanced Reconstruction
Akash Gupta, Abhishek Aich, Kevin Rodriguez +2
While machine learning approaches have shown remarkable performance in biomedical image analysis, most of these methods rely on high-quality and accurate imaging data. However, col…
ALANET: Adaptive Latent Attention Network forJoint Video Deblurring and Interpolation
Akash Gupta, Abhishek Aich, Amit K. Roy-Chowdhury
Existing works address the problem of generating high frame-rate sharp videos by separately learning the frame deblurring and frame interpolation modules. Most of these approaches…
Adversarial Knowledge Transfer from Unlabeled Data
Akash Gupta, Rameswar Panda, Sujoy Paul +2
While machine learning approaches to visual recognition offer great promise, most of the existing methods rely heavily on the availability of large quantities of labeled training d…
Non-Adversarial Video Synthesis with Learned Priors
Abhishek Aich, Akash Gupta, Rameswar Panda +3
Most of the existing works in video synthesis focus on generating videos using adversarial learning. Despite their success, these methods often require input reference frame or fai…