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visual-interaction-networks-pytorch's Introduction

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

visual-interaction-networks-pytorch's People

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codeaudit danpechi tony32769 github30 shubhampachori12110095 jaedukseo bestlin yes7rose fxia22 kelvinson waleedgondal anupamandroid 3dmm-icme2023 weiyunchen godpeterliu coolsunxu ambei andy12392 syyunn vivianliangb tiansn-n raynbowy23 trendingtechnology nilsagor ethicalsecurity-agency

visual-interaction-networks-pytorch's Issues

Data??

Hi

From the physics_engine.py we get a .mp4. The program is expecting images??

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.

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