activity
20192023
most citedComputational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization

14 citations · 24 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2023★ 1 cited

Alchemist: Parametric Control of Material Properties with Diffusion Models

Prafull Sharma, Varun Jampani, Yuanzhen Li +5

We propose a method to control material attributes of objects like roughness, metallic, albedo, and transparency in real images. Our method capitalizes on the generative prior of t…

cs.CV2023★ 1 cited

Materialistic: Selecting Similar Materials in Images

Prafull Sharma, Julien Philip, Michaël Gharbi +3

Separating an image into meaningful underlying components is a crucial first step for both editing and understanding images. We present a method capable of selecting the regions of…

cs.CV2022

SAR-to-EO Image Translation with Multi-Conditional Adversarial Networks

Armando Cabrera, Miriam Cha, Prafull Sharma +1

This paper explores the use of multi-conditional adversarial networks for SAR-to-EO image translation. Previous methods condition adversarial networks only on the input SAR. We sho…

cs.CV2022★ 8 cited

Neural Groundplans: Persistent Neural Scene Representations from a Single Image

Prafull Sharma, Ayush Tewari, Yilun Du +7

We present a method to map 2D image observations of a scene to a persistent 3D scene representation, enabling novel view synthesis and disentangled representation of the movable an…

cs.CV2021

What You Can Learn by Staring at a Blank Wall

Prafull Sharma, Miika Aittala, Yoav Y. Schechner +4

We present a passive non-line-of-sight method that infers the number of people or activity of a person from the observation of a blank wall in an unknown room. Our technique analyz…

cs.CV2019★ 14 cited

Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization

Miika Aittala, Prafull Sharma, Lukas Murmann +4

We recover a video of the motion taking place in a hidden scene by observing changes in indirect illumination in a nearby uncalibrated visible region. We solve this problem by fact…