Anagh Malik

I am a first year Computer Science PhD student at the University of Toronto, supervised by David Lindell. I am affiliated with both the Toronto Computational Imaging Group and the Vector Institute.

Before this I did my MRes at the Dyson Robotics Lab at Imperial College London, where I worked on self-supervised segmentation, under the supervision of Andrew Davison and Ronald Clark.

anagh [at] cs [dot] toronto [dot] edu

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I am broadly interested in scene understanding. That is using visual cues to infer properites of objects and scenes.

Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction
Anagh Malik, Parsa Mirdehghan, Sotiris Nousias, Kiriakos N. Kutulakos, David B. Lindell
NeurIPS, 2023   (Spotlight)
project page / video / arXiv

We introduce a method to do novel view lidar synthesis, allowing sparse view scene reconstruction.

clean-usnob Exploring Neural Representations for Self-Supervised Segmentation
Anagh Malik
Master's Thesis, 2022

We develop a method for self-supervised segmentation through agreement and self-distillation.

clean-usnob SegDIP: The Unreasonable Effectiveness of Randomly-Initialized CNNs for Interactive Segmentation
Anagh Malik, Shuaifeng Zhi, Marwan Taher, Ronald Clark, Andrew Davison

We train an encoder-decoder network to map from xy-coordinates to RGB values and semantic classes, allowing real-time segmentation of an image.

clean-usnob Strategies for the Iterated Prisoner’s Dilemma
Anagh Malik
arXiv, 2020

We explore Zero-Determinant strategies for the Iterated Priosner's Dilemma, pointing out flaws in the current literature.

Template stolen from Jon Barron's website.