Divam Gupta — accepted AI-conference papers

2024

Codec Avatar Studio: Paired Human Captures for Complete, Driveable, and Generalizable Avatars

Julieta Martinez, Emily Kim, Javier Romero, Timur Bagautdinov, Shunsuke Saito, Shoou-I Yu +64

NeurIPS 2024poster

To build photorealistic avatars that users can embody, human modelling must be complete (cover the full body), driveable (able to reproduce the current motion and appearance from the user), and generalizable (_i.e._, easily adaptable to novel identities). Towards these goals, _paired_ captures, that…

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2020

Unsupervised Clustering using Pseudo-semi-supervised Learning

Divam Gupta, Ramachandran Ramjee, Nipun Kwatra, Muthian Sivathanu

ICLR 2020poster

In this paper, we propose a framework that leverages semi-supervised models to improve unsupervised clustering performance. To leverage semi-supervised models, we first need to automatically generate labels, called pseudo-labels. We find that prior approaches for generating pseudo-labels hurt cluste…

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