papers

Publications (12)

cs.CV2025

MARBLE: Material Recomposition and Blending in CLIP-Space

Ta-Ying Cheng, Prafull Sharma, Mark Boss +1

Editing materials of objects in images based on exemplar images is an active area of research in computer vision and graphics. We propose MARBLE, a method for performing material b…

cs.AI2026

Digital Red Queen: Adversarial Program Evolution in Core War with LLMs

Akarsh Kumar, Ryan Bahlous-Boldi, Prafull Sharma +4

Large language models (LLMs) are increasingly being used to evolve solutions to problems in many domains, in a process inspired by biological evolution. However, unlike biological…

cs.CV2023

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.CV2023

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.CL2026

Evaluating Language Models' Evaluations of Games

Katherine M. Collins, Cedegao E. Zhang, Graham Todd +9

Reasoning is not just about solving problems -- it is also about evaluating which problems are worth solving at all. Evaluations of artificial intelligence (AI) systems primarily f…

cs.CV2024

ZeST: Zero-Shot Material Transfer from a Single Image

Ta-Ying Cheng, Prafull Sharma, Andrew Markham +2

We propose ZeST, a method for zero-shot material transfer to an object in the input image given a material exemplar image. ZeST leverages existing diffusion adapters to extract imp…

cs.CV2023

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.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.AI2025

Assessing Adaptive World Models in Machines with Novel Games

Lance Ying, Katherine M. Collins, Prafull Sharma +11

Human intelligence exhibits a remarkable capacity for rapid adaptation and effective problem-solving in novel and unfamiliar contexts. We argue that this profound adaptability is f…

cs.AI2026

AI Gamestore: Scalable, Open-Ended Evaluation of Machine General Intelligence with Human Games

Lance Ying, Ryan Truong, Prafull Sharma +9

Rigorously evaluating machine intelligence against the broad spectrum of human general intelligence has become increasingly important and challenging in this era of rapid technolog…

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.CV2019

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…