This's an implementation of deepmind Visual Interaction Networks paper using pytorch

Related tags

Deep Learning machine-learning computer-vision deep-learning physics pytorch convolutional-neural-networks deepmind video-prediction-models nerual-network visual-interaction-networks
Overview

Visual-Interaction-Networks

An implementation of Deepmind visual interaction networks in Pytorch.

Introduction

For the purpose of understanding the challenge of relational reasoning. they publised VIN that involves predicting the future in a physical scene. From just a glance, humans can infer not only what objects are where, but also what will happen to them over the upcoming seconds, minutes and even longer in some cases. For example, if you kick a football against a wall, your brain predicts what will happen when the ball hits the wall and how their movements will be affected afterwards (the ball will ricochet at a speed proportional to the kick and - in most cases - the wall will remain where it is).

Architecture

Data

I used I@jaesik817 physics engine to generate the data.

Just run the physics_engine.py

Usage

Main Dependencies

Python 3.5
pytorch 0.3
numpy 1.13.1

RUN

  • Edit configration file to meet your need.
  • Run vin.py

References

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Comments
  • Get test results?

    Get test results?

    Hi, I'm confused about this line: https://github.com/MrGemy95/visual-interaction-networks-pytorch/blob/master/train.py#L115

    If the xy_estimated is never updated, how to get meaningful test results for the make_image2 function?

    opened by HaozhiQi 0
  • Parts missing from Visual Encoder

    Parts missing from Visual Encoder

    Hi, this code doesn't converge for me. Have you tried reproducing the results? There are some modules missing from the Visual Encoder Part in the code, more specifically Image Encoder Pair layers.

    opened by waleedgondal 0
Owner
Mahmoud Gamal Salem
MSc. in AI at university of Guelph and Vector Institute. AI intern @samsung
Mahmoud Gamal Salem
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