Cody Reading

I am a PhD student at Simon Fraser University supervised by Andrea Tagliasacchi, My research interests are in 3D computer vision, generative models, and computer graphics. and. I am currently interested in using machine learning for 3D content creation and editing.

I received my master's degree from the University of Toronto supervised by Steven Waslander, and received my bachelor's degree from the University of Waterloo. I also worked at MARZ developing Vanity AI, an AI solution for facial editing for VFX.

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We introduce a post-hoc framework to evaluate uncertainty in any pre-trained NeRF without modifying the training process.

We introduce BANF, a method for band-limited frequency decomposition in neural fields.

We introduce the Interaction Transformer to 3D multi-object tracking to generate discriminative object representations for data association.

We estimate categorical depth distributions to project image feature information to 3D space for improved 3D monocular object detection.

We generate a synthetic dataset for semantic segmentation based on GTA V.

Implementing novel techniques in 3D content creation and generative models, involving optimizing NeRF and 3D Gaussian representations with diffusion guidance.

Developed a facial de-aging tool Vanity AI designed for VFX applications, achieving 300x speed up compared to traditional VFX workflows.

Innovated methodologies in autonomous vehicle 3D perception, achieving 1st and 2nd place on 3D monocular object detection and 3D multi-object tracking benchmarks respectively

Developed a vehicle trajectory generation library within the NVIDIA DriveWorks SDK using C++ to generate a sequence of vehicle poses from GPS, IMU, and CAN sensor data

Developed semantic segmentation training infrastructure to support unified training of the SegNet and FCN methods on the Cityscapes, Playing-for-data, and Synthia datasets.

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Last updated: April, 2024