2 citations · 3 across the 10 of their papers we have counts for
5 papers · 1 filter
Incremental Multi-Scene Modeling via Continual Neural Graphics Primitives
Prajwal Singh, Ashish Tiwari, Gautam Vashishtha +1
Neural radiance fields (NeRF) have revolutionized photorealistic rendering of novel views for 3D scenes. Despite their growing popularity and efficiency as 3D resources, NeRFs face…
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…
DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated Images
Ashish Tiwari, Shanmuganathan Raman
Photometric stereo, a problem of recovering 3D surface normals using images of an object captured under different lightings, has been of great interest and importance in computer v…