1 citations · 1 across the 4 of their papers we have counts for
6 papers
Bias for Action: Video Implicit Neural Representations with Bias Modulation
Alper Kayabasi, Anil Kumar Vadathya, Guha Balakrishnan +1
We propose a new continuous video modeling framework based on implicit neural representations (INRs) called ActINR. At the core of our approach is the observation that INRs can be…
Optimal HDR and Depth from Dual Cameras
Pradyumna Chari, Anil Kumar Vadathya, Kaushik Mitra
Dual camera systems have assisted in the proliferation of various applications, such as optical zoom, low-light imaging and High Dynamic Range (HDR) imaging. In this work, we explo…
A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections
Anil Kumar Vadathya, Sharath Girish, Kaushik Mitra
Light field presents a rich way to represent the 3D world by capturing the spatio-angular dimensions of the visual signal. However, the popular way of capturing light field (LF) vi…
Solving Inverse Computational Imaging Problems using Deep Pixel-level Prior
Akshat Dave, Anil Kumar Vadathya, Ramana Subramanyam +2
Signal reconstruction is a challenging aspect of computational imaging as it often involves solving ill-posed inverse problems. Recently, deep feed-forward neural networks have led…
Learning Light Field Reconstruction from a Single Coded Image
Anil Kumar Vadathya, Saikiran Cholleti, Gautham Ramajayam +2
Light field imaging is a rich way of representing the 3D world around us. However, due to limited sensor resolution capturing light field data inherently poses spatio-angular resol…
Compressive Image Recovery Using Recurrent Generative Model
Akshat Dave, Anil Kumar Vadathya, Kaushik Mitra
Reconstruction of signals from compressively sensed measurements is an ill-posed problem. In this paper, we leverage the recurrent generative model, RIDE, as an image prior for com…