1 citations · 1 across the 9 of their papers we have counts for
9 papers
LIPIDS: Learning-based Illumination Planning In Discretized (Light) Space for Photometric Stereo
Ashish Tiwari, Mihir Sutariya, Shanmuganathan Raman
Photometric stereo is a powerful method for obtaining per-pixel surface normals from differently illuminated images of an object. While several methods address photometric stereo w…
MERLiN: Single-Shot Material Estimation and Relighting for Photometric Stereo
Ashish Tiwari, Satoshi Ikehata, Shanmuganathan Raman
Photometric stereo typically demands intricate data acquisition setups involving multiple light sources to recover surface normals accurately. In this paper, we propose MERLiN, an…
SS-SfP:Neural Inverse Rendering for Self Supervised Shape from (Mixed) Polarization
Ashish Tiwari, Shanmuganathan Raman
We present a novel inverse rendering-based framework to estimate the 3D shape (per-pixel surface normals and depth) of objects and scenes from single-view polarization images, the…
Learning Robust Deep Visual Representations from EEG Brain Recordings
Prajwal Singh, Dwip Dalal, Gautam Vashishtha +2
Decoding the human brain has been a hallmark of neuroscientists and Artificial Intelligence researchers alike. Reconstruction of visual images from brain Electroencephalography (EE…
Search Me Knot, Render Me Knot: Embedding Search and Differentiable Rendering of Knots in 3D
Aalok Gangopadhyay, Paras Gupta, Tarun Sharma +2
We introduce the problem of knot-based inverse perceptual art. Given multiple target images and their corresponding viewing configurations, the objective is to find a 3D knot-based…
EEG2IMAGE: Image Reconstruction from EEG Brain Signals
Prajwal Singh, Pankaj Pandey, Krishna Miyapuram +1
Reconstructing images using brain signals of imagined visuals may provide an augmented vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) technolo…