Pavel Tokmakov

Orcid: 0000-0003-2043-6242

According to our database1, Pavel Tokmakov authored at least 31 papers between 2013 and 2024.

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Bibliography

2024
pix2gestalt: Amodal Segmentation by Synthesizing Wholes.
CoRR, 2024

Understanding Video Transformers via Universal Concept Discovery.
CoRR, 2024

2023
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models.
CoRR, 2023

Zero-1-to-3: Zero-shot One Image to 3D Object.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Breaking the "Object" in Video Object Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Tracking Through Containers and Occluders in the Wild.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Object Discovery from Motion-Guided Tokens.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Object Permanence Emerges in a Random Walk along Memory.
Proceedings of the International Conference on Machine Learning, 2022

Discovering Objects that Can Move.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Learning to Track with Object Permanence.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Unlocking the Full Potential of Small Data With Diverse Supervision.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Unsupervised Learning of Video Representations via Dense Trajectory Clustering.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

TAO: A Large-Scale Benchmark for Tracking Any Object.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Learning to Segment Moving Objects.
Int. J. Comput. Vis., 2019

Learning Generalizable Representations via Diverse Supervision.
CoRR, 2019

Learning to Track Any Object.
CoRR, 2019

A Study on Action Detection in the Wild.
CoRR, 2019

Towards Segmenting Everything That Moves.
CoRR, 2019

Towards Segmenting Anything That Moves.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Learning Compositional Representations for Few-Shot Recognition.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Towards Latent Attribute Discovery From Triplet Similarities.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

A Structured Model for Action Detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Learning from motion. (Apprentissage à partir du mouvement).
PhD thesis, 2018

2017
Relational linear programming.
Artif. Intell., 2017

Learning Video Object Segmentation with Visual Memory.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Learning Motion Patterns in Videos.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Weakly-Supervised Semantic Segmentation Using Motion Cues.
Proceedings of the Computer Vision - ECCV 2016, 2016

2014
Relational Linear Programs.
CoRR, 2014

2013
One click mining: interactive local pattern discovery through implicit preference and performance learning.
Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics, 2013


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