most citedThe Atari Grand Challenge Dataset

21 citations · 34 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2019

Large-Scale Object Mining for Object Discovery from Unlabeled Video

Aljosa Osep, Paul Voigtlaender, Jonathon Luiten +2

This paper addresses the problem of object discovery from unlabeled driving videos captured in a realistic automotive setting. Identifying recurring object categories in such raw v…

cs.CV201710 cited

Large-Scale Object Discovery and Detector Adaptation from Unlabeled Video

Aljoša Ošep, Paul Voigtlaender, Jonathon Luiten +2

We explore object discovery and detector adaptation based on unlabeled video sequences captured from a mobile platform. We propose a fully automatic approach for object mining from…

cs.CV2017

Track, then Decide: Category-Agnostic Vision-based Multi-Object Tracking

Aljoša Ošep, Wolfgang Mehner, Paul Voigtlaender +1

The most common paradigm for vision-based multi-object tracking is tracking-by-detection, due to the availability of reliable detectors for several important object categories such…

cs.CV20171 cited

Online Adaptation of Convolutional Neural Networks for Video Object Segmentation

Paul Voigtlaender, Bastian Leibe

We tackle the task of semi-supervised video object segmentation, i.e. segmenting the pixels belonging to an object in the video using the ground truth pixel mask for the first fram…

cs.AI201721 cited

The Atari Grand Challenge Dataset

Vitaly Kurin, Sebastian Nowozin, Katja Hofmann +2

Recent progress in Reinforcement Learning (RL), fueled by its combination, with Deep Learning has enabled impressive results in learning to interact with complex virtual environmen…

cs.CV20172 cited

Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters

Lucas Beyer, Stefan Breuers, Vitaly Kurin +1

With the rise of end-to-end learning through deep learning, person detectors and re-identification (ReID) models have recently become very strong. Multi-camera multi-target (MCMT)…