1 citations · 2 across the 14 of their papers we have counts for
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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…
Single Image LDR to HDR Conversion using Conditional Diffusion
Dwip Dalal, Gautam Vashishtha, Prajwal Singh +1
Digital imaging aims to replicate realistic scenes, but Low Dynamic Range (LDR) cameras cannot represent the wide dynamic range of real scenes, resulting in under-/overexposed imag…
A Graph Neural Network Approach for Temporal Mesh Blending and Correspondence
Aalok Gangopadhyay, Abhinav Narayan Harish, Prajwal Singh +1
We have proposed a self-supervised deep learning framework for solving the mesh blending problem in scenarios where the meshes are not in correspondence. To solve this problem, we…
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…