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University of Toronto, Waabi
- Toronto
- https://andreibarsan.github.io
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Magical Rust patterns laid out and simplified
SLEDGE: Synthesizing Simulation Environments for Driving Agents with Generative Models
A Spotify player in the terminal with full feature parity
LightGlue: Local Feature Matching at Light Speed (ICCV 2023)
Code for "Street Gaussians for Modeling Dynamic Urban Scenes"
A unified framework for 3D content generation.
Pytorch implementation of NetVlad including training on Pittsburgh.
Simulating shitty network connections so you can build better systems.
The open-source tool for building high-quality datasets and computer vision models
This is the Rust course used by the Android team at Google. It provides you the material to quickly teach Rust.
A powerful and easy to use Python framework for experiment tracking and incremental computing
A system for quickly generating training data with weak supervision
A multidimensional discrete hill climbing heuristic search algorithm implemented in Python
The Python SDK for the Pit30M large scale visual localization dataset.
Streamlit Component for rendering Folium maps
Official implementation of "Learning to Generate Realistic LiDAR Point Clouds" (ECCV 2022)
High-throughput simulation platform for Artificial Intelligence reseach
A library for differentiable nonlinear optimization
Lightning fast C++/CUDA neural network framework
Mitsuba 3: A Retargetable Forward and Inverse Renderer
µStreamer - Lightweight and fast MJPEG-HTTP streamer
[CVPR 2021, Oral] PREDATOR: Registration of 3D Point Clouds with Low Overlap.