SfM-Net: Learning of Structure and Motion from Video

SfM-Net: A smart way to see depth and motion in everyday videos

SfM-Net is a clever system that looks at video and figures out 3D shape and movement, just from the frames.
It learns to guess depth, track camera motion, and notice moving objects, while also making simple masks for where things move — called segmentation.
The model warps one frame to the next and checks if pixels line up, so it can learn even when no labels are given.
Sometimes it gets depth right, often it recovers how the camera turned or moved, and many times it separates moving things from the rest, even though nobody showed it examples.
You can train it with full data, or only with camera info, or with nothing but the video itself.
That makes it flexible and cheap to teach.
The result: ordinary videos become a source of 3D cues and motion, useful for phones, robots, or anyone curious to make sense of a moving scene.
Try to imagine video that teaches itself, it almost feels like giving eyes to a computer, and it kind of does.

Read article comprehensive review in Paperium.net:
SfM-Net: Learning of Structure and Motion from Video

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