kaanakan/slamp
SLAMP: Stochastic Latent Appearance and Motion Prediction
This project helps researchers in computer vision predict future frames in a video sequence. It takes a series of past video frames as input and generates a probable sequence of future frames, even when there's randomness in the motion or appearance. This is useful for researchers developing AI systems that need to anticipate events or understand dynamic scenes.
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Use this if you are a computer vision researcher working on video prediction and need a method to generate plausible future frames from a given past sequence, especially for complex real-world datasets like KITTI or Cityscapes.
Not ideal if you are looking for a plug-and-play solution for general video editing or consumer-facing applications, as this tool requires familiarity with model training and evaluation in a research context.
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38
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3
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 10, 2023
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