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ViP: Video Platform for PyTorch

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arxiv 1910.02793 v1 pith:VU3WHPF7 submitted 2019-10-07 cs.CV cs.LGeess.IV

Madan Ravi Ganesh , Eric Hofesmann , Nathan Louis , Jason Corso This is my paper · ORCID
classification cs.CVcs.LGeess.IV
keywords videoplatformproblemallowdomainsmodelspytorchsupports
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This work presents the Video Platform for PyTorch (ViP), a deep learning-based framework designed to handle and extend to any problem domain based on videos. ViP supports (1) a single unified interface applicable to all video problem domains, (2) quick prototyping of video models, (3) executing large-batch operations with reduced memory consumption, and (4) easy and reproducible experimental setups. ViP's core functionality is built with flexibility and modularity in mind to allow for smooth data flow between different parts of the platform and benchmarking against existing methods. In providing a software platform that supports multiple video-based problem domains, we allow for more cross-pollination of models, ideas and stronger generalization in the video understanding research community.

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