•1 min read•from Machine Learning
Any implementations similar to D4RT? [D]
Our take
DeepMind's recent D4RT paper presents a groundbreaking approach to understanding the world in four dimensions by reconstructing point clouds from 2D video data. This technique not only estimates camera poses but also generates dynamic 3D representations, such as visualizing a dog walking on a beach in real-time. While the model itself hasn't been released, several open-source implementations are emerging that aspire to replicate similar capabilities. Exploring these alternatives can empower developers and researchers to leverage innovative 3D reconstruction techniques for their projects.
Deepmind released a paper on D4RT at the start of this year which crucially enabled a “4D” understanding of the world via structure from motion and generating:
1. Point cloud reconstruction from 2D videos (not static scenes)
2. Camera pose estimation
You could pass in a video of a dog walking on a beach and it would estimate the 3d representation of the beach and the dog at any point in time.
They did not release the model though. Are there any open source, available implementations of anything similar now?
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