About Me

Hi! I am Makarand Tapaswi, a PostDoctoral Fellow at Inria Paris, France, working in the Willow group with Ivan Laptev and Josef Sivic. Broadly, my work revolves around machine understanding of videos and language. In particular, I enjoy working with movies and TV series, especially teaching machines about human behavior and analyzing storylines.

Previously, I was with the Machine Learning group, University of Toronto, working with Sanja Fidler. Two large projects that we created were MovieGraphs on understanding peoples' behaviors and interactions, and Movie4D on studying special effects in movies with the aim to bring 4D cinema to everyone's home.

I completed my PhD at the Computer Vision for Human Computer Interaction (CVHCI) lab, Karlsruhe Institute of Technology, Germany. I introduced novel problems such as alignment of books with movies, plot synopses (from Wikipedia) with TV episodes, their visualization inspired by XKCD, and the first story question-answering challenge: MovieQA. I also worked on clustering and identifying characters in videos to allow for semantic video analysis.

If you have any questions, please feel free to contact me.

Latest News

Paper at CVPR 2020

Learning Interactions and Relationships between Movie Characters ( Download)

Two papers at ICCV 2019

Ball Cluster Learning estimates the number of clusters and partitions ( Download); HowTo100M a dataset with 130 million paired video clip and captions useful for unsupervised learning ( Download).

Best Paper Award at FG 2019

for our paper on self-supervised face clustering with Vivek, Saquib, and Rainer!

Media coverage!

HowTo100M: Antoine interviews for a Podcast at Data Skeptic.

MovieGraphs: UofT News, phys.org

Movie4D: UofT News, Inquisitr, CBC Radio interview