Object Level Visual Reasoning in Videos

European Conference on Computer Vision (ECCV)


Human activity recognition is typically addressed by training models to detect key concepts like global and local motion, features related to object classes present in the scene, as well as features related to the global context. The next open challenges in activity recognition require a level of understanding that pushes beyond this, requiring fine distinctions and a detailed comprehension of the interactions between actors and objects in a scene. We propose a model capable of learning to reason about semantically meaningful spatio-temporal interactions in videos. Key to our approach is the choice of performing this reasoning on an object level through the integration of state of the art object instance segmentation networks. This allows the model to learn detailed spatial interactions that exist at a semantic, object-interaction relevant level. We evaluated our method on three standard datasets: the TwentyBN Something-Something dataset, the VLOG dataset and the EPIC Kitchens dataset, and achieve state of the art results on both. Finally, we also show visualizations of the interactions learned by the model, which illustrate object classes and their interactions corresponding to different activity classes.

Related Publications

All Publications

Open Source Evolutionary Structured Optimization

Jeremy Rapin, Pauline Bennet, Emmanuel Centeno, Daniel Haziza, Antoine Moreau, Olivier Teytaud

Evolutionary Computation Software Systems Workshop at ​GECCO - July 9, 2020

Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning

Tianyu Li, Nathan Lambert, Roberto Calandra, Franziska Meier, Akshara Rai

ICRA - June 1, 2020

Large Scale Audiovisual Learning of Sounds with Weakly Labeled Data

Haytham M. Fayek, Anurag Kumar

IJCAI - July 11, 2020

Efficient Bimanual Manipulation Using Learned Task Schemas

No Authors Listed

ICRA - May 31, 2020

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy