Ntumba Elie, Nsampi

I am a Ph.D. student at the Max Planck Institute For Informatics and Saarland University, where i am fortunate to be supervised by Dr. Thomas Leimkühler. Prior to joining MPI-INF i obtained a masters in Computer Science from Northwestern Polytechnical University where i was supervised by Professor Qing Wang.

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My research lies at the intersection of Computer Vision, Computer Graphics, and Machine Learning. I'm particularly interested in exploring problems that connect these areas. Currently, I focus on Implicit Neural Representations for graphics, with an emphasis on incorporating physical priors to address inverse problems.

Open to Collaborations : If you're working on related problems or interested in implicit neural representations and physics-informed methods, please don't hesitate to reach out.

We propose an algorithm to learn a continuous gaussian scale space field from a single image

We propose an algorithm to perform efficient continuous convolution of neural fields.

We propose an algorithm for image harmonization alongside with a new dataset.

We propose an algoritm to decompose the any-to-any relighting problem, into three sub-problems and propose three networks to solve each one independently.

We propose a method to constrain a deep network to learn an exposure-invariant representation, such that images of different exposure degradation level result in the same internal representation.

We propose a shadow guidance network, which when plugged into an any-to-any relighting pipeline improves the quality of generated shadows.

Thanks to Jon Barron for the website template.
Last updated July 2025.