Katerina Fragkiadaki

I am interested in building machines that understand the stories that videos portray, and, inversely, in using videos to teach machines about the world. The pen-ultimate goal is to build a machine that understands movie plots, and the ultimate goal is to build a machine that would want to watch Bergman over this.

I am an Assistant Professor in the Machine Learning Department at Carnegie Mellon. Prior to joining MLD's faculty I spent three wonderful years as a post doctoral researcher first at UC Berkeley working with Jitendra Malik and then at Google Research in Mountain View working with the video group. I completed my Ph.D. in GRASP, UPenn with Jianbo Shi. I did my undergraduate studies at the National Technical University of Athens and before that I was in Crete.

Dear prospective graduate students: There is no need to email, please submit your application to our School following the links here: MLD Ph.D. or R.I. Ph.D.

8107 Gates Hillman
Carnegie Mellon University
Pittsburgh, PA, 15213
katef 'at' cs.cmu.edu
Admin: Laura Winter, lwinter@andrew.cmu.edu

News:

Teaching

Deep Reinforcement Learning and Control Spring 2022
Deep Reinforcement Learning and Control Fall 2021
Deep Reinforcement Learning and Control Spring 2021
Deep Reinforcement Learning and Control Fall 2020
Deep Reinforcement Learning and Control Spring 2020
Deep Reinforcement Learning and Control Fall 2019
Deep Reinforcement Learning and Control Spring 2019
Deep Reinforcement Learning and Control Fall 2018
Deep Reinforcement Learning and Control Spring 2017
Language Grounding for Vision and Control Fall 2017

Research

Teaching machines to appreciate Bergman is a hard problem, in fact, most people fail to do so. Thus, it is a very long term goal of our research. Meanwhile, we are working on teaching machines basic common sense. Our recent works use recurrent nets with 3D representation bottlenecks that disentangle camera motion from appearance, while being optimized end-to-end for a final task, such as view prediction or 3D object detection. In this way, our models learn object permanence, size constancy, occlusions and dis-occlusion relationships, useful for 3D object detection, affordance learning and language grounding.

Selected Publications

Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Clouds
Ayush Jain, Nikolaos Gkanatsios, Ishita Mediratta, Katerina Fragkiadaki
ECCV 2022
paper| | project page with code
TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors
Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley, Paul Schydlo, Michael J. Tarr, Saurabh Gupta, Katerina Fragkiadaki
ECCV 2022
paper| | project page with code
Particle Videos Revisited: Tracking Through Occlusions Using Point Trajectories
Adam W. Harley, Zhaoyuan Fang, Katerina Fragkiadaki
ECCV 2022, oral
paper | project page with code
Generating Fast and Slow: Scene Decomposition via Reconstruction
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki
arXiv 2022
paper
Visually-Grounded Library of Behaviors for Manipulating Diverse Objects across Diverse Configurations and Views
Jingyun Yang*, Hsiao-Yu Fish Tung*, Yunchu Zhang*, Gaurav Pathak, Ashwini Pokle, Christopher G Atkeson, Katerina Fragkiadaki
CoRL 2021
paper | project page with code
Disentangling 3D Prototypical Networks for Few-Shot Concept Learning
Mihir Prabhudesai*, Shamit Lal*, Darshan Patil*, Hsiao-Yu Tung, Adam Harley, Katerina Fragkiadaki
ICLR 2021
paper | project page with code
HyperDynamics: Generating Expert Dynamics Models by Observation
Zhou Xian, Shamit Lal, Hsiao-Yu Tung, Emmanouil Antonios Platanios, Katerina Fragkiadaki
ICLR 2021
paper | project page with code
Track, Check, Repeat: An EM Approach to Unsupervised Tracking
Adam W. Harley, Yiming Zuo, Jing Wen, Ayush Mangal, Shubhankar Potdar, Ritwick Chaudhry, Katerina Fragkiadaki
CVPR 2021
paper | project page with code
Move to See Better: Self-Improving Embodied Object Detection
Zhaoyuan Fang, Ayush Jain, Gabriel Sarch, Adam W. Harley, Katerina Fragkiadaki
BMVC 2021
paper | project page
CoCoNets: Continuous Contrastive 3D Scene Representations
Shamit Lal, Mihir Prabhudesai, Ishita Mediratta, Adam W. Harley, Katerina Fragkiadaki
CVPR 2021
paper | project page
Tracking Emerges by Looking Around Static Scenes, with Neural 3D Mapping
Adam W. Harley, Shrinidhi K. Lakshmikanth, Paul Schydlo, Katerina Fragkiadaki
ECCV 2020
paper
Embodied Language Grounding with Implicit 3D Visual Feature Representations
Mihir Prabhudesai*, Hsiao-Yu Fish Tung*, Syed Ashar Javed*, Maximilian Sieb, Adam W. Harley, Katerina Fragkiadaki
CVPR 2020
paper | project page
Epipolar Transformers
Yihui He, Rui Yan, Katerina Fragkiadaki, Shoou-I Yu
CVPR 2020
paper | project page
Graph-structured Visual Imitation
Xian Zhou*, Max Sieb*, Audrey Huang, Oliver Kroemer, Katerina Fragkiadaki
CoRL 2019
paper | project page with code
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping
Adam W. Harley, Fangyu Li, Shrinidhi K. Lakshmikanth, Xian Zhou, Hsiao-Yu Fish Tung, Katerina Fragkiadaki
ICLR 2020
paper | project page with code
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks
Hsiao-Yu Fish Tung, Ricson Cheng, Katerina Fragkiadaki
CVPR 2019, oral presentation
paper | project page with code
Model Learning for Look-ahead Exploration in Continuous Control
Arpit Agarwal, Katharina Muelling and Katerina Fragkiadaki
AAAI 2019, oral presentation
paper | project page with code
Data Dreaming for Object Detection: Learning Object-Centric State Representations for Visual Imitation
Maximilian Sieb and Katerina Fragkiadaki
Humanoids 2018, oral presentation
paper | slides
Reinforcement Learning of Active Vision for Manipulating Objects under Occlusionss
Ricson Cheng, Arpit Agarwal, and Katerina Fragkiadaki
CoRL 2018
paper | slides | code
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
Ricson Cheng, Ziyan Wang, and Katerina Fragkiadaki
NIPS 2018
paper
Reward Learning from Narrated Demonstrations
Fish Tung, Adam Harley, Liang-Kang Huang, Katerina Fragkiadaki
CVPR 2018
paper | bibtex
Depth-adaptive Computational Policies for Efficient Visual Tracking
Chris Ying, Katerina Fragkiadaki
EMMCVPR 2017
paper | bibtex
Self-supervised Learning of Motion Capture
Hsiao-Yu Fish Tung, Wei Tung, Ersin Yumer, Katerina Fragkiadaki
NIPS 2017, spotlight
paper | bibtex | code
Adversarial Inverse Graphics Networks: Learning 2D-to-3D Lifting and mage-to-Image Translation from Unpaired Supervision
Hsiao-Yu Fish Tung, Adam Harley, William Seto and Katerina Fragkiadaki
ICCV 2017
paper | bibtex | code
SfM-Net: Learning of Structure and Motion from Video
Sudheendra Vijayanarasimhan, Susanna Ricco, Cordelia Schmid, Rahul Sukthankar and Katerina Fragkiadaki
arxiv
Motion Prediction Under Multimodality with Conditional Stochastic Networks
Katerina Fragkiadaki, Jonathan Huang, Alex Alemi, Sudheendra Vijayanarasimhan, Susanna Ricco and Rahul Sukthankar
arxiv | video results
Learning Feature Hierarchies from Long-Range Temporal Associations in Videos
Panna Felsen, Katerina Fragkiadaki, Jitendra Malik and Alexei Efros
Workshop on Transfer and Multi-task Learning, in conjunction with NIPS 2015
paper
Learning Predictive Visual Models of Physics for Playing Billiards
Katerina Fragkiadaki*, Pulkit Agrawal*, Sergey Levine and Jitendra Malik
ICLR 2016
paper | project page
Recurrent Network Models for Human Dynamics
Katerina Fragkiadaki, Sergey Levine, Panna Felsen and Jitendra Malik
ICCV 2015
paper | project page
Human Pose Estimation with Iterative Error Feedback
Joao Carreira, Pulkit Agrawal, Katerina Fragkiadaki, and Jitendra Malik
arXiv
paper|project page with code
Learning to Segment Moving Objects in Videos
Katerina Fragkiadaki, Pablo Arbelaez, Panna Felsen and Jitendra Malik
CVPR 2015
paper | poster | bibtex | project page with code
Grouping-Based Low-Rank Video Completion and 3D Reconstruction
Katerina Fragkiadaki, Marta Salas, Pablo Arbelaez, and Jitendra Malik
NIPS 2014
paper | poster | bibtex | project page with code
Two Granularity Tracking: Mediating Trajectory and Detection Graphs for Tracking under Occlusions
Katerina Fragkiadaki, Weiyu Zhang, Geng Zhang, and Jianbo Shi
ECCV 2012
paper | poster | bibtex | project page with code
Video Segmentation by tracing Discontinuities in a Trajectory Embedding
Katerina Fragkiadaki, Geng Zhang, and Jianbo Shi
CVPR 2012
paper | poster | bibtex | project page with code
Detection-free Tracking: Exploiting Motion and Topology for Segmenting and Tracking under Entanglement
Katerina Fragkiadaki and Jianbo Shi
CVPR 2011
paper | poster | bibtex

Current Students

Adam Harley, R.I. Ph.D.
Mihir Prabhudesai R.I. Ph.D., (co-advised with Deepak Pathak)
Xian Zhou, R.I. Ph.D.
Gabriel Sarch , Neuroscience Institute and Center for the Neural Basis of Cognition Ph.D. student, co-advised with Mike Tarr
Brian Yang ,R.I. Ph.D., co-advised with Jeff Schneider
Nikos Gkanasios R.I. Ph.D.
Ayush Jain R.I. MSR
Zhaoyuan Fang, MSR, R.I.
Mayank Singh, MSR, R.I.
Yunchu Zhang, MSR, R.I.

Alumni

Fish Tung, MLD Ph.D., now post doc in M.I.T.
Ricson Chen, undergrad CSD
Ziyan Wang, MSR
Shamit Lal, MSCV
Yiming Zuo , MSR, now Ph.D. in Princeton
Max Sieb, MSR
Arpit Agarwal, MSR
Henry Huang, MSML
Chris Ying, MSML
Yijie Wang, MSML
Darshan Patil , undergraduate CSD, now in MILA Ph.D.
Gaurav Pathak, research associate
Shrinidhi Kowshika Lakshmikanth, research associate
Ashwini Polke, MLD Ph.D.

MISC