Object-Centric Video Prediction via Decoupling of Object Dynamics and Interactions

• URL: http://arxiv.org/abs/2302.11850v2
• Date: Mon, 31 Jul 2023 09:35:08 GMT
• Title: Object-Centric Video Prediction via Decoupling of Object Dynamics and Interactions
• Authors: Angel Villar-Corrales, Ismail Wahdan and Sven Behnke
• Abstract summary: We propose a novel framework for the task of object-centric video prediction, i.e., extracting the structure of a video sequence, as well as modeling objects dynamics and interactions from visual observations. With the goal of learning meaningful object representations, we propose two object-centric video predictor (OCVP) transformer modules, which de-couple processing of temporal dynamics and object interactions. In our experiments, we show how our object-centric prediction framework utilizing our OCVP predictors outperforms object-agnostic video prediction models on two different datasets.
• Score: 27.112210225969733
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a novel framework for the task of object-centric video prediction, i.e., extracting the compositional structure of a video sequence, as well as modeling objects dynamics and interactions from visual observations in order to predict the future object states, from which we can then generate subsequent video frames. With the goal of learning meaningful spatio-temporal object representations and accurately forecasting object states, we propose two novel object-centric video predictor (OCVP) transformer modules, which decouple the processing of temporal dynamics and object interactions, thus presenting an improved prediction performance. In our experiments, we show how our object-centric prediction framework utilizing our OCVP predictors outperforms object-agnostic video prediction models on two different datasets, while maintaining consistent and accurate object representations.

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