Amit Vikram Singh — accepted AI-conference papers

2026

ShapeAR: Generating Editable Shape Layers via Autoregressive Diffusion

Souymodip Chakraborty, Ankur Singh, Amit Vikram Singh, Vineet Batra, Ankit Phogat

CVPR 2026

We present ShapeAR, a novel autoregressive latent diffusion framework that decomposes raster images into editable, artist-like vector shape layers. Unlike conventional raster-to-SVG methods that rely on boundary tracing or joint path optimisation, ShapeAR generates non-overlapping RGBA shape layers

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2020

Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning

Chandrashekar Lakshminarayanan, Amit Vikram Singh

NeurIPS 2020poster

Rectified linear unit (ReLU) activations can also be thought of as 'gates', which, either pass or stop their pre-activation input when they are 'on' (when the pre-activation input is positive) or 'off' (when the pre-activation input is negative) respectively. A deep neural network (DNN) with ReLU ac…

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