Laura Leal-Taixé

According to our database, Laura Leal-Taixé authored at least 117 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation.

Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé

CoRR, 2024

Better Call SAL: Towards Learning to Segment Anything in Lidar.

Aljosa Osep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, Laura Leal-Taixé

CoRR, 2024

The NeRFect Match: Exploring NeRF Features for Visual Localization.

Qunjie Zhou, Maxim Maximov, Or Litany, Laura Leal-Taixé

CoRR, 2024

SeMoLi: What Moves Together Belongs Together.

Jenny Seidenschwarz, Aljosa Osep, Francesco Ferroni, Simon Lucey, Laura Leal-Taixé

CoRR, 2024

2023

The Group Loss++: A Deeper Look Into Group Loss for Deep Metric Learning.

Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé

IEEE Trans. Pattern Anal. Mach. Intell., 2023

NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation.

Tim Meinhardt, Matt Feiszli, Yuchen Fan, Laura Leal-Taixé, Rakesh Ranjan

CoRR, 2023

Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis.

Maxim Maximov, Tim Meinhardt, Ismail Elezi, Zoe Papakipos, Caner Hazirbas, Cristian Canton-Ferrer, Laura Leal-Taixé

CoRR, 2023

Lidar Panoptic Segmentation and Tracking without Bells and Whistles.

Abhinav Agarwalla, Xuhua Huang, Jason Ziglar, Francesco Ferroni, Laura Leal-Taixé, James Hays, Aljosa Osep, Deva Ramanan

IROS, 2023

Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation.

Cristiano Saltori, Aljosa Osep, Elisa Ricci, Laura Leal-Taixé

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Simple Cues Lead to a Strong Multi-Object Tracker.

Jenny Seidenschwarz, Guillem Brasó, Victor Castro Serrano, Ismail Elezi, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Soft Augmentation for Image Classification.

Yang Liu, Shen Yan, Laura Leal-Taixé, James Hays, Deva Ramanan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

G-MSM: Unsupervised Multi-Shape Matching with Graph-Based Affinity Priors.

Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Unifying Short and Long-Term Tracking with Graph Hierarchies.

Orcun Cetintas, Guillem Brasó, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Staged Contact-Aware Global Human Motion Forecasting.

Luca Scofano, Alessio Sampieri, Elisabeth Schiele, Edoardo De Matteis, Laura Leal-Taixé, Fabio Galasso

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images.

Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiao Xiang Zhu

IEEE Trans. Geosci. Remote. Sens., 2022

Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles.

Lucas Nunes, Xieyuanli Chen, Rodrigo Marcuzzi, Aljosa Osep, Laura Leal-Taixé, Cyrill Stachniss, Jens Behley

IEEE Robotics Autom. Lett., 2022

Learn to Predict Sets Using Feed-Forward Neural Networks.

Hamid Rezatofighi, Tianyu Zhu, Roman Kaskman, Farbod T. Motlagh, Javen Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Multi-Object Tracking and Segmentation Via Neural Message Passing.

Guillem Brasó, Orcun Cetintas, Laura Leal-Taixé

Int. J. Comput. Vis., 2022

DeVIS: Making Deformable Transformers Work for Video Instance Segmentation.

Adrià Caelles, Tim Meinhardt, Guillem Brasó, Laura Leal-Taixé

CoRR, 2022

Simple Cues Lead to a Strong Multi-Object Tracker.

Jenny Seidenschwarz, Guillem Brasó, Ismail Elezi, Laura Leal-Taixé

CoRR, 2022

Learning to Discover and Detect Objects.

Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?

Patrick Dendorfer, Vladimir Yugay, Aljosa Osep, Laura Leal-Taixé

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes.

Peter Kocsis, Peter Súkeník, Guillem Brasó, Matthias Nießner, Laura Leal-Taixé, Ismail Elezi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment.

Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Is Geometry Enough for Matching in Visual Localization?

Qunjie Zhou, Sérgio Agostinho, Aljosa Osep, Laura Leal-Taixé

Proceedings of the Computer Vision - ECCV 2022, 2022

PolarMOT: How Far Can Geometric Relations Take us in 3D Multi-object Tracking?

Aleksandr Kim, Guillem Brasó, Aljosa Osep, Laura Leal-Taixé

Proceedings of the Computer Vision - ECCV 2022, 2022

DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation.

Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çaglar Senaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Forecasting from LiDAR via Future Object Detection.

Neehar Peri, Jonathon Luiten, Mengtian Li, Aljosa Osep, Laura Leal-Taixé, Deva Ramanan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

TrackFormer: Multi-Object Tracking with Transformers.

Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph Feichtenhofer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Opening up Open World Tracking.

Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Deva Ramanan, Bastian Leibe, Aljosa Osep, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Text2Pos: Text-to-Point-Cloud Cross-Modal Localization.

Manuel Kolmet, Qunjie Zhou, Aljosa Osep, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection.

Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, José M. Álvarez

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

A Unified Framework for Implicit Sinkhorn Differentiation.

Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Decoupling Identity and Visual Quality for Image and Video Anonymization.

Maxim Maximov, Ismail Elezi, Laura Leal-Taixé

Proceedings of the Computer Vision - ACCV 2022, 2022

2021

HOTA: A Higher Order Metric for Evaluating Multi-object Tracking.

Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip H. S. Torr, Andreas Geiger, Laura Leal-Taixé, Bastian Leibe

Int. J. Comput. Vis., 2021

MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking.

Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, Laura Leal-Taixé

Int. J. Comput. Vis., 2021

Towards Reducing Labeling Cost in Deep Object Detection.

Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, José M. Álvarez

CoRR, 2021

DeepLab2: A TensorFlow Library for Deep Labeling.

Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixé, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen

CoRR, 2021

The 2021 Image Similarity Dataset and Challenge.

Matthijs Douze, Giorgos Tolias, Ed Pizzi, Zoë Papakipos, Lowik Chanussot, Filip Radenovic, Tomás Jenícek, Maxim Maximov, Laura Leal-Taixé, Ismail Elezi, Ondrej Chum, Cristian Canton-Ferrer

CoRR, 2021

STEP: Segmenting and Tracking Every Pixel.

Mark Weber, Jun Xie, Maxwell D. Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljosa Osep, Laura Leal-Taixé, Liang-Chieh Chen

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space.

Lukas Kondmann, Aysim Toker, Marc Rußwurm, Andrés Camero, Devis Peressuti, Grega Milcinski, Pierre-Philippe Mathieu, Nicolas Longépé, Timothy Davis, Giovanni Marchisio, Laura Leal-Taixé, Xiaoxiang Zhu

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning.

Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

EagerMOT: 3D Multi-Object Tracking via Sensor Fusion.

Aleksandr Kim, Aljosa Osep, Laura Leal-Taixé

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Learning Intra-Batch Connections for Deep Metric Learning.

Jenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé

Proceedings of the 38th International Conference on Machine Learning, 2021

A Single-Stage, Bottom-up Approach for Occluded VIS using Spatio-temporal Embeddings.

Ali Athar, Sabarinath Mahadevan, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?

Matteo Fabbri, Guillem Brasó, Gianluca Maugeri, Orcun Cetintas, Riccardo Gasparini, Aljosa Osep, Simone Calderara, Laura Leal-Taixé, Rita Cucchiara

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction.

Patrick Dendorfer, Sven Elflein, Laura Leal-Taixé

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation.

Guillem Brasó, Nikita Kister, Laura Leal-Taixé

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

(Just) A Spoonful of Refinements Helps the Registration Error Go Down.

Sérgio Agostinho, Aljosa Osep, Alessio Del Bue, Laura Leal-Taixé

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Patch2Pix: Epipolar-Guided Pixel-Level Correspondences.

Qunjie Zhou, Torsten Sattler, Laura Leal-Taixé

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization.

Aysim Toker, Qunjie Zhou, Maxim Maximov, Laura Leal-Taixé

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

4D Panoptic LiDAR Segmentation.

Mehmet Aygun, Aljosa Osep, Mark Weber, Maxim Maximov, Cyrill Stachniss, Jens Behley, Laura Leal-Taixé

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Learning temporal coherence via self-supervision for GAN-based video generation.

Mengyu Chu, You Xie, Jonas Mayer, Laura Leal-Taixé, Nils Thuerey

ACM Trans. Graph., 2020

Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams Using Machine Learning.

Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler

Remote. Sens., 2020

MOT20: A benchmark for multi object tracking in crowded scenes.

Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé

CoRR, 2020

Lake Ice Monitoring with Webcams and Crowd-Sourced Images.

Rajanie Prabha, Manu Tom, Mathias Rothermel, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler

CoRR, 2020

Learn to Predict Sets Using Feed-Forward Neural Networks.

Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid

CoRR, 2020

HistoNet: Predicting size histograms of object instances.

Kishan Sharma, Moritz Gold, Christian Zurbruegg, Laura Leal-Taixé, Jan Dirk Wegner

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Make One-Shot Video Object Segmentation Efficient Again.

Tim Meinhardt, Laura Leal-Taixé

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Shells: Unsupervised Shape Correspondence with Optimal Transport.

Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Planning from Images with Deep Latent Gaussian Process Dynamics.

Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé, Jörg Stückler

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

To Learn or Not to Learn: Visual Localization from Essential Matrices.

Qunjie Zhou, Torsten Sattler, Marc Pollefeys, Laura Leal-Taixé

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

The Group Loss for Deep Metric Learning.

Ismail Elezi, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé

Proceedings of the Computer Vision - ECCV 2020, 2020

STEm-Seg: Spatio-Temporal Embeddings for Instance Segmentation in Videos.

Ali Athar, Sabarinath Mahadevan, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe

Proceedings of the Computer Vision - ECCV 2020, 2020

How to Train Your Deep Multi-Object Tracker.

Yihong Xu, Aljosa Osep, Yutong Ban, Radu Horaud, Laura Leal-Taixé, Xavier Alameda-Pineda

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Focus on Defocus: Bridging the Synthetic to Real Domain Gap for Depth Estimation.

Maxim Maximov, Kevin Galim, Laura Leal-Taixé

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks.

Maxim Maximov, Ismail Elezi, Laura Leal-Taixé

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning a Neural Solver for Multiple Object Tracking.

Guillem Brasó, Laura Leal-Taixé

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Making a Case for 3D Convolutions for Object Segmentation in Videos.

Sabarinath Mahadevan, Ali Athar, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe, Sebastian Hennen

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation.

Patrick Dendorfer, Aljosa Osep, Laura Leal-Taixé

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

Video Object Segmentation without Temporal Information.

Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool

IEEE Trans. Pattern Anal. Mach. Intell., 2019

CVPR19 Tracking and Detection Challenge: How crowded can it get?

Patrick Dendorfer, Seyed Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé

CoRR, 2019

Towards Generalizing Sensorimotor Control Across Weather Conditions.

Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Deep Appearance Maps.

Maxim Maximov, Tobias Ritschel, Laura Leal-Taixé, Mario Fritz

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Tracking Without Bells and Whistles.

Philipp Bergmann, Tim Meinhardt, Laura Leal-Taixé

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Understanding the Limitations of CNN-Based Absolute Camera Pose Regression.

Torsten Sattler, Qunjie Zhou, Marc Pollefeys, Laura Leal-Taixé

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Temporally Coherent GANs for Video Super-Resolution (TecoGAN).

Mengyu Chu, You Xie, Laura Leal-Taixé, Nils Thuerey

CoRR, 2018

Modular Vehicle Control for Transferring Semantic Information to Unseen Weather Conditions using GANs.

Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé

CoRR, 2018

Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks.

Seyed Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid

CoRR, 2018

Lifting Layers: Analysis and Applications.

Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller

Proceedings of the Computer Vision - ECCV 2018, 2018

Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs.

Emanuel Laude, Jan-Hendrik Lange, Jonas Schüpfer, Csaba Domokos, Laura Leal-Taixé, Frank R. Schmidt, Bjoern Andres, Daniel Cremers

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Fusion of Head and Full-Body Detectors for Multi-Object Tracking.

Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs.

Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Deep Depth from Focus.

Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers

Proceedings of the Computer Vision - ACCV 2018, 2018

2017

Deep Learning for Computer Vision (Dagstuhl Seminar 17391).

Daniel Cremers, Laura Leal-Taixé, René Vidal

Dagstuhl Reports, 2017

Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking.

Laura Leal-Taixé, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth

CoRR, 2017

Improvements to Frank-Wolfe optimization for multi-detector multi-object tracking.

Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn

CoRR, 2017

Deep Depth From Focus.

Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers

CoRR, 2017

Image-Based Localization Using LSTMs for Structured Feature Correlation.

Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers

Proceedings of the IEEE International Conference on Computer Vision, 2017

One-Shot Video Object Segmentation.

Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Image-based Localization with Spatial LSTMs.

Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers

CoRR, 2016

MOT16: A Benchmark for Multi-Object Tracking.

Anton Milan, Laura Leal-Taixé, Ian D. Reid, Stefan Roth, Konrad Schindler

CoRR, 2016

Tracking with multi-level features.

Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn, Konrad Schindler

CoRR, 2016

Automatic tracking of vessel-like structures from a single starting point.

Dário Augusto Borges Oliveira, Laura Leal-Taixé, Raul Queiroz Feitosa, Bodo Rosenhahn

Comput. Medical Imaging Graph., 2016

Learning by Tracking: Siamese CNN for Robust Target Association.

Laura Leal-Taixé, Cristian Canton-Ferrer, Konrad Schindler

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016

2015

Holistic Scene Understanding (Dagstuhl Seminar 15081).

Jiri Matas, Vittorio Murino, Bodo Rosenhahn, Laura Leal-Taixé

Dagstuhl Reports, 2015

MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking.

Laura Leal-Taixé, Anton Milan, Ian D. Reid, Stefan Roth, Konrad Schindler

CoRR, 2015

Solving Multiple People Tracking in a Minimum Cost Arborescence.

Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn

Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision Workshops, 2015

Pose Estimation of Object Categories in Videos Using Linear Programming.

Michele Fenzi, Laura Leal-Taixé, Konrad Schindler, Jörn Ostermann

Proceedings of the 2015 IEEE Winter Conference on Applications of Computer Vision, 2015

Continuous Pose Estimation with a Spatial Ensemble of Fisher Regressors.

Michele Fenzi, Laura Leal-Taixé, Jörn Ostermann, Tinne Tuytelaars

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Joint tracking and segmentation of multiple targets.

Anton Milan, Laura Leal-Taixé, Konrad Schindler, Ian D. Reid

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Multiple object tracking with context awareness.

Laura Leal-Taixé

PhD thesis, 2014

Multiple object tracking with context awareness.

Laura Leal-Taixé

CoRR, 2014

Efficient Multiple People Tracking Using Minimum Cost Arborescences.

Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn

Proceedings of the Pattern Recognition - 36th German Conference, 2014

Learning an Image-Based Motion Context for Multiple People Tracking.

Laura Leal-Taixé, Michele Fenzi, Alina Kuznetsova, Bodo Rosenhahn, Silvio Savarese

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Real-Time Sign Language Recognition Using a Consumer Depth Camera.

Alina Kuznetsova, Laura Leal-Taixé, Bodo Rosenhahn

Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories.

Michele Fenzi, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Pedestrian Interaction in Tracking: The Social Force Model and Global Optimization Methods.

Laura Leal-Taixé, Bodo Rosenhahn

Proceedings of the Modeling, Simulation and Visual Analysis of Crowds, 2013

2012

3D Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized RANSAC and Model Updating.

Michele Fenzi, Ralf Dragon, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann

Proceedings of the Pattern Recognition, 2012

Branch-and-price global optimization for multi-view multi-target tracking.

Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Data-Driven Manifolds for Outdoor Motion Capture.

Gerard Pons-Moll, Laura Leal-Taixé, Juergen Gall, Bodo Rosenhahn

Proceedings of the Outdoor and Large-Scale Real-World Scene Analysis - 15th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany, June 26, 2011

Exploiting Pedestrian Interaction via Global Optimization and Social Behaviors.

Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn

Proceedings of the Outdoor and Large-Scale Real-World Scene Analysis - 15th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany, June 26, 2011

Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker.

Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Outdoor human motion capture using inverse kinematics and von mises-fisher sampling.

Gerard Pons-Moll, Andreas Baak, Juergen Gall, Laura Leal-Taixé, Meinard Müller, Hans-Peter Seidel, Bodo Rosenhahn

Proceedings of the IEEE International Conference on Computer Vision, 2011

Efficient and Robust Shape Matching for Model Based Human Motion Capture.

Gerard Pons-Moll, Laura Leal-Taixé, Tri Truong, Bodo Rosenhahn

Proceedings of the Pattern Recognition - 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31, 2011

2010

Understanding What we Cannot See: Automatic Analysis of 4D Digital In-Line Holographic Microscopy Data.

Laura Leal-Taixé, Matthias Heydt, Axel Rosenhahn, Bodo Rosenhahn

Proceedings of the Video Processing and Computational Video, 2010

Classification of Swimming Microorganisms Motion Patterns in 4D Digital In-Line Holography Data.

Laura Leal-Taixé, Matthias Heydt, Sebastian Weiße, Axel Rosenhahn, Bodo Rosenhahn

Proceedings of the Pattern Recognition, 2010