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ORCIDLaura Leal-Taixé
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- affiliation: Technical University of Munich, Department of Informatics, Germany
- affiliation: Leibniz University of Hannover, TNT, Germany
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2020 – today
- 2024
[c81]Jenny Seidenschwarz, Aljosa Osep, Francesco Ferroni, Simon Lucey, Laura Leal-Taixé:
SeMoLi: What Moves Together Belongs Together. CVPR 2024: 14685-14694- [c80]Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé:
SatSynth: Augmenting Image-Mask Pairs Through Diffusion Models for Aerial Semantic Segmentation. CVPR 2024: 27685-27695 - [c79]Aljosa Osep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, Laura Leal-Taixé:
Better Call SAL: Towards Learning to Segment Anything in Lidar. ECCV (39) 2024: 71-90 - [c78]Linyan Yang, Lukas Hoyer, Mark Weber, Tobias Fischer, Dengxin Dai, Laura Leal-Taixé, Marc Pollefeys, Daniel Cremers, Luc Van Gool:
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. ECCV (39) 2024: 329-346 - [c77]Maxim Maximov, Tim Meinhardt, Zoe Papakipos, Caner Hazirbas, Cristian Canton, Laura Leal-Taixé:
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-Identification via Full-Body Person Synthesis. FG 2024: 1-10 - [i87]Jenny Seidenschwarz, Aljosa Osep, Francesco Ferroni, Simon Lucey
, Laura Leal-Taixé:
SeMoLi: What Moves Together Belongs Together. CoRR abs/2402.19463 (2024) - [i86]Qunjie Zhou, Maxim Maximov, Or Litany, Laura Leal-Taixé:
The NeRFect Match: Exploring NeRF Features for Visual Localization. CoRR abs/2403.09577 (2024) - [i85]Aljosa Osep, Tim Meinhardt, Francesco Ferroni, Neehar Peri, Deva Ramanan, Laura Leal-Taixé:
Better Call SAL: Towards Learning to Segment Anything in Lidar. CoRR abs/2403.13129 (2024) - [i84]Aysim Toker, Marvin Eisenberger, Daniel Cremers, Laura Leal-Taixé:
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation. CoRR abs/2403.16605 (2024) - [i83]Orcun Cetintas, Tim Meinhardt, Guillem Brasó, Laura Leal-Taixé:
SPAMming Labels: Efficient Annotations for the Trackers of Tomorrow. CoRR abs/2404.11426 (2024) - [i82]Linyan Yang, Lukas Hoyer, Mark Weber, Tobias Fischer, Dengxin Dai, Laura Leal-Taixé, Marc Pollefeys, Daniel Cremers, Luc Van Gool:
MICDrop: Masking Image and Depth Features via Complementary Dropout for Domain-Adaptive Semantic Segmentation. CoRR abs/2408.16478 (2024) - [i81]Jenny Seidenschwarz, Qunjie Zhou, Bardienus Pieter Duisterhof, Deva Ramanan, Laura Leal-Taixé:
DynOMo: Online Point Tracking by Dynamic Online Monocular Gaussian Reconstruction. CoRR abs/2409.02104 (2024) - [i80]Anirudh S. Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu, Laura Leal-Taixé, Shu Kong, Deva Ramanan, Aljosa Osep:
Lidar Panoptic Segmentation in an Open World. CoRR abs/2409.14273 (2024) - 2023
- [j11]Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé:
The Group Loss++: A Deeper Look Into Group Loss for Deep Metric Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2505-2518 (2023) - [c76]Luca Scofano, Alessio Sampieri, Elisabeth Schiele, Edoardo De Matteis, Laura Leal-Taixé, Fabio Galasso:
Staged Contact-Aware Global Human Motion Forecasting. BMVC 2023: 589-594 - [c75]Jenny Seidenschwarz, Guillem Brasó, Victor Castro Serrano, Ismail Elezi, Laura Leal-Taixé:
Simple Cues Lead to a Strong Multi-Object Tracker. CVPR 2023: 13813-13823 - [c74]Yang Liu, Shen Yan, Laura Leal-Taixé, James Hays, Deva Ramanan:
Soft Augmentation for Image Classification. CVPR 2023: 16241-16250 - [c73]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-Based Affinity Priors. CVPR 2023: 22762-22772 - [c72]Orcun Cetintas, Guillem Brasó, Laura Leal-Taixé:
Unifying Short and Long-Term Tracking with Graph Hierarchies. CVPR 2023: 22877-22887 - [c71]Cristiano Saltori, Aljosa Osep, Elisa Ricci, Laura Leal-Taixé:
Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation. ICCV 2023: 196-206 - [c70]Abhinav Agarwalla, Xuhua Huang, Jason Ziglar, Francesco Ferroni, Laura Leal-Taixé, James Hays, Aljosa Osep, Deva Ramanan:
Lidar Panoptic Segmentation and Tracking without Bells and Whistles. IROS 2023: 7667-7674 - [i79]Cristiano Saltori, Aljosa Osep, Elisa Ricci, Laura Leal-Taixé:
Walking Your LiDOG: A Journey Through Multiple Domains for LiDAR Semantic Segmentation. CoRR abs/2304.11705 (2023) - [i78]Maxim Maximov, Tim Meinhardt, Ismail Elezi, Zoe Papakipos, Caner Hazirbas, Cristian Canton-Ferrer, Laura Leal-Taixé:
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis. CoRR abs/2306.11710 (2023) - [i77]Tim Meinhardt, Matt Feiszli, Yuchen Fan, Laura Leal-Taixé, Rakesh Ranjan:
NOVIS: A Case for End-to-End Near-Online Video Instance Segmentation. CoRR abs/2308.15266 (2023) - [i76]Luca Scofano, Alessio Sampieri, Elisabeth Schiele, Edoardo De Matteis, Laura Leal-Taixé, Fabio Galasso:
Staged Contact-Aware Global Human Motion Forecasting. CoRR abs/2309.08947 (2023) - [i75]Abhinav Agarwalla, Xuhua Huang, Jason Ziglar, Francesco Ferroni, Laura Leal-Taixé, James Hays, Aljosa Osep, Deva Ramanan:
Lidar Panoptic Segmentation and Tracking without Bells and Whistles. CoRR abs/2310.12464 (2023) - 2022
- [j10]Guillem Brasó, Orcun Cetintas, Laura Leal-Taixé:
Multi-Object Tracking and Segmentation Via Neural Message Passing. Int. J. Comput. Vis. 130(12): 3035-3053 (2022) - [j9]Hamid Rezatofighi, Tianyu Zhu, Roman Kaskman, Farbod T. Motlagh, Javen Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9011-9025 (2022) - [j8]Lucas Nunes, Xieyuanli Chen, Rodrigo Marcuzzi, Aljosa Osep, Laura Leal-Taixé, Cyrill Stachniss, Jens Behley:
Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles. IEEE Robotics Autom. Lett. 7(4): 8713-8720 (2022) - [j7]Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiao Xiang Zhu:
Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022) - [c69]Maxim Maximov, Ismail Elezi, Laura Leal-Taixé:
Decoupling Identity and Visual Quality for Image and Video Anonymization. ACCV (6) 2022: 510-526 - [c68]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CVPR 2022: 499-508 - [c67]Manuel Kolmet, Qunjie Zhou, Aljosa Osep, Laura Leal-Taixé:
Text2Pos: Text-to-Point-Cloud Cross-Modal Localization. CVPR 2022: 6677-6686 - [c66]Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph Feichtenhofer:
TrackFormer: Multi-Object Tracking with Transformers. CVPR 2022: 8834-8844 - [c65]Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, José M. Álvarez:
Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection. CVPR 2022: 14472-14481 - [c64]Neehar Peri, Jonathon Luiten, Mengtian Li, Aljosa Osep, Laura Leal-Taixé, Deva Ramanan:
Forecasting from LiDAR via Future Object Detection. CVPR 2022: 17181-17190 - [c63]Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Deva Ramanan, Bastian Leibe, Aljosa Osep, Laura Leal-Taixé:
Opening up Open World Tracking. CVPR 2022: 19023-19033 - [c62]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:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CVPR 2022: 21126-21135 - [c61]Aleksandr Kim, Guillem Brasó, Aljosa Osep, Laura Leal-Taixé:
PolarMOT: How Far Can Geometric Relations Take us in 3D Multi-object Tracking? ECCV (22) 2022: 41-58 - [c60]Qunjie Zhou, Sérgio Agostinho, Aljosa Osep, Laura Leal-Taixé:
Is Geometry Enough for Matching in Visual Localization? ECCV (10) 2022: 407-425 - [c59]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. IROS 2022: 3777-3784 - [c58]Peter Kocsis, Peter Súkeník, Guillem Brasó, Matthias Nießner, Laura Leal-Taixé, Ismail Elezi:
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes. NeurIPS 2022 - [c57]Patrick Dendorfer, Vladimir Yugay, Aljosa Osep, Laura Leal-Taixé:
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking? NeurIPS 2022 - [c56]Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep:
Learning to Discover and Detect Objects. NeurIPS 2022 - [i74]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:
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. CoRR abs/2203.12560 (2022) - [i73]Qunjie Zhou, Sérgio Agostinho, Aljosa Osep, Laura Leal-Taixé:
Is Geometry Enough for Matching in Visual Localization? CoRR abs/2203.12979 (2022) - [i72]Manuel Kolmet, Qunjie Zhou, Aljosa Osep, Laura Leal-Taixé:
Text2Pos: Text-to-Point-Cloud Cross-Modal Localization. CoRR abs/2203.15125 (2022) - [i71]Neehar Peri, Jonathon Luiten, Mengtian Li, Aljosa Osep, Laura Leal-Taixé, Deva Ramanan:
Forecasting from LiDAR via Future Object Detection. CoRR abs/2203.16297 (2022) - [i70]Ismail Elezi, Jenny Seidenschwarz, Laurin Wagner, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé:
The Group Loss++: A deeper look into group loss for deep metric learning. CoRR abs/2204.01509 (2022) - [i69]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Florian Bernard, Daniel Cremers:
A Unified Framework for Implicit Sinkhorn Differentiation. CoRR abs/2205.06688 (2022) - [i68]Jenny Seidenschwarz, Guillem Brasó, Ismail Elezi, Laura Leal-Taixé:
Simple Cues Lead to a Strong Multi-Object Tracker. CoRR abs/2206.04656 (2022) - [i67]Guillem Brasó, Orcun Cetintas, Laura Leal-Taixé:
Multi-Object Tracking and Segmentation via Neural Message Passing. CoRR abs/2207.07454 (2022) - [i66]Adrià Caelles, Tim Meinhardt, Guillem Brasó, Laura Leal-Taixé:
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation. CoRR abs/2207.11103 (2022) - [i65]Aleksandr Kim, Guillem Brasó, Aljosa Osep, Laura Leal-Taixé:
PolarMOT: How Far Can Geometric Relations Take Us in 3D Multi-Object Tracking? CoRR abs/2208.01957 (2022) - [i64]Mariia Gladkova, Nikita Korobov, Nikolaus Demmel, Aljosa Osep, Laura Leal-Taixé, Daniel Cremers:
DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment. CoRR abs/2209.14965 (2022) - [i63]Peter Kocsis, Peter Súkeník, Guillem Brasó, Matthias Nießner, Laura Leal-Taixé, Ismail Elezi:
The Unreasonable Effectiveness of Fully-Connected Layers for Low-Data Regimes. CoRR abs/2210.05657 (2022) - [i62]Patrick Dendorfer, Vladimir Yugay, Aljosa Osep, Laura Leal-Taixé:
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking? CoRR abs/2210.07681 (2022) - [i61]Vladimir Fomenko, Ismail Elezi, Deva Ramanan, Laura Leal-Taixé, Aljosa Osep:
Learning to Discover and Detect Objects. CoRR abs/2210.10774 (2022) - [i60]Yang Liu, Shen Yan, Laura Leal-Taixé, James Hays, Deva Ramanan:
Soft Augmentation for Image Classification. CoRR abs/2211.04625 (2022) - [i59]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
G-MSM: Unsupervised Multi-Shape Matching with Graph-based Affinity Priors. CoRR abs/2212.02910 (2022) - [i58]Orcun Cetintas, Guillem Brasó, Laura Leal-Taixé:
Unifying Short and Long-Term Tracking with Graph Hierarchies. CoRR abs/2212.03038 (2022) - 2021
- [j6]Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip H. S. Torr, Andreas Geiger, Laura Leal-Taixé, Bastian Leibe:
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking. Int. J. Comput. Vis. 129(2): 548-578 (2021) - [j5]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking. Int. J. Comput. Vis. 129(4): 845-881 (2021) - [c55]Qunjie Zhou, Torsten Sattler, Laura Leal-Taixé:
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences. CVPR 2021: 4669-4678 - [c54]Mehmet Aygun, Aljosa Osep, Mark Weber, Maxim Maximov, Cyrill Stachniss, Jens Behley, Laura Leal-Taixé:
4D Panoptic LiDAR Segmentation. CVPR 2021: 5527-5537 - [c53]Aysim Toker, Qunjie Zhou, Maxim Maximov, Laura Leal-Taixé:
Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization. CVPR 2021: 6488-6497 - [c52]Sérgio Agostinho, Aljosa Osep, Alessio Del Bue, Laura Leal-Taixé:
(Just) A Spoonful of Refinements Helps the Registration Error Go Down. ICCV 2021: 6088-6097 - [c51]Matteo Fabbri, Guillem Brasó, Gianluca Maugeri, Orcun Cetintas, Riccardo Gasparini, Aljosa Osep, Simone Calderara, Laura Leal-Taixé, Rita Cucchiara:
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking? ICCV 2021: 10829-10839 - [c50]Guillem Brasó, Nikita Kister, Laura Leal-Taixé:
The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation. ICCV 2021: 11833-11843 - [c49]Patrick Dendorfer, Sven Elflein, Laura Leal-Taixé:
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction. ICCV 2021: 13138-13147 - [c48]Ali Athar, Sabarinath Mahadevan, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe:
A Single-Stage, Bottom-up Approach for Occluded VIS using Spatio-temporal Embeddings. ICCVW 2021: 3851-3855 - [c47]Jenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé:
Learning Intra-Batch Connections for Deep Metric Learning. ICML 2021: 9410-9421 - [c46]Aleksandr Kim, Aljosa Osep, Laura Leal-Taixé:
EagerMOT: 3D Multi-Object Tracking via Sensor Fusion. ICRA 2021: 11315-11321 - [c45]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. ICRA 2021: 14360-14366 - [c44]Lukas Kondmann, Aysim Toker, Marc Rußwurm, Andrés Camero, Devis Peressutti, Grega Milcinski, Pierre-Philippe Mathieu, Nicolas Longépé, Timothy Davis, Giovanni Marchisio, Laura Leal-Taixé, Xiaoxiang Zhu:
DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space. NeurIPS Datasets and Benchmarks 2021 - [c43]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:
STEP: Segmenting and Tracking Every Pixel. NeurIPS Datasets and Benchmarks 2021 - [i57]Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph Feichtenhofer:
TrackFormer: Multi-Object Tracking with Transformers. CoRR abs/2101.02702 (2021) - [i56]Jenny Seidenschwarz, Ismail Elezi, Laura Leal-Taixé:
Learning Intra-Batch Connections for Deep Metric Learning. CoRR abs/2102.07753 (2021) - [i55]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:
STEP: Segmenting and Tracking Every Pixel. CoRR abs/2102.11859 (2021) - [i54]Mehmet Aygün, Aljosa Osep, Mark Weber, Maxim Maximov, Cyrill Stachniss, Jens Behley, Laura Leal-Taixé:
4D Panoptic LiDAR Segmentation. CoRR abs/2102.12472 (2021) - [i53]Patrick Wenzel, Torsten Schön, Laura Leal-Taixé, Daniel Cremers:
Vision-Based Mobile Robotics Obstacle Avoidance With Deep Reinforcement Learning. CoRR abs/2103.04727 (2021) - [i52]Aysim Toker, Qunjie Zhou, Maxim Maximov, Laura Leal-Taixé:
Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization. CoRR abs/2103.06818 (2021) - [i51]Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Aljosa Osep, Deva Ramanan, Bastian Leibe, Laura Leal-Taixé:
Opening up Open-World Tracking. CoRR abs/2104.11221 (2021) - [i50]Aleksandr Kim, Aljosa Osep, Laura Leal-Taixé:
EagerMOT: 3D Multi-Object Tracking via Sensor Fusion. CoRR abs/2104.14682 (2021) - [i49]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:
The 2021 Image Similarity Dataset and Challenge. CoRR abs/2106.09672 (2021) - [i48]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:
DeepLab2: A TensorFlow Library for Deep Labeling. CoRR abs/2106.09748 (2021) - [i47]Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixé, José M. Álvarez:
Towards Reducing Labeling Cost in Deep Object Detection. CoRR abs/2106.11921 (2021) - [i46]Sérgio Agostinho, Aljosa Osep, Alessio Del Bue, Laura Leal-Taixé:
(Just) A Spoonful of Refinements Helps the Registration Error Go Down. CoRR abs/2108.03257 (2021) - [i45]Patrick Dendorfer, Sven Elflein, Laura Leal-Taixé:
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction. CoRR abs/2108.09274 (2021) - [i44]Matteo Fabbri, Guillem Brasó, Gianluca Maugeri, Orcun Cetintas, Riccardo Gasparini, Aljosa Osep, Simone Calderara, Laura Leal-Taixé, Rita Cucchiara:
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking? CoRR abs/2108.09518 (2021) - [i43]Lukas Kondmann, Aysim Toker, Sudipan Saha, Bernhard Schölkopf, Laura Leal-Taixé, Xiaoxiang Zhu:
Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images. CoRR abs/2110.02068 (2021) - [i42]Guillem Brasó, Nikita Kister, Laura Leal-Taixé:
The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation. CoRR abs/2110.05132 (2021) - 2020
- [j4]Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler:
Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams Using Machine Learning. Remote. Sens. 12(21): 3555 (2020) - [j3]Mengyu Chu, You Xie, Jonas Mayer, Laura Leal-Taixé, Nils Thuerey:
Learning temporal coherence via self-supervision for GAN-based video generation. ACM Trans. Graph. 39(4): 75 (2020) - [c42]Patrick Dendorfer, Aljosa Osep, Laura Leal-Taixé:
Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation. ACCV (2) 2020: 405-420 - [c41]Sabarinath Mahadevan, Ali Athar, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe, Sebastian Hennen:
Making a Case for 3D Convolutions for Object Segmentation in Videos. BMVC 2020 - [c40]Maxim Maximov, Kevin Galim, Laura Leal-Taixé:
Focus on Defocus: Bridging the Synthetic to Real Domain Gap for Depth Estimation. CVPR 2020: 1068-1077 - [c39]Maxim Maximov, Ismail Elezi, Laura Leal-Taixé:
CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks. CVPR 2020: 5446-5455 - [c38]Guillem Brasó, Laura Leal-Taixé:
Learning a Neural Solver for Multiple Object Tracking. CVPR 2020: 6246-6256 - [c37]Yihong Xu, Aljosa Osep, Yutong Ban, Radu Horaud, Laura Leal-Taixé, Xavier Alameda-Pineda:
How to Train Your Deep Multi-Object Tracker. CVPR 2020: 6786-6795 - [c36]Ali Athar, Sabarinath Mahadevan, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe:
STEm-Seg: Spatio-Temporal Embeddings for Instance Segmentation in Videos. ECCV (11) 2020: 158-177 - [c35]Ismail Elezi, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé:
The Group Loss for Deep Metric Learning. ECCV (7) 2020: 277-294 - [c34]Qunjie Zhou, Torsten Sattler, Marc Pollefeys, Laura Leal-Taixé:
To Learn or Not to Learn: Visual Localization from Essential Matrices. ICRA 2020: 3319-3326 - [c33]Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé, Jörg Stückler:
Planning from Images with Deep Latent Gaussian Process Dynamics. L4DC 2020: 640-650 - [c32]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. NeurIPS 2020 - [c31]Tim Meinhardt, Laura Leal-Taixé:
Make One-Shot Video Object Segmentation Efficient Again. NeurIPS 2020 - [c30]Kishan Sharma, Moritz Gold, Christian Zurbruegg, Laura Leal-Taixé, Jan Dirk Wegner:
HistoNet: Predicting size histograms of object instances. WACV 2020: 3626-3634 - [i41]Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Learn to Predict Sets Using Feed-Forward Neural Networks. CoRR abs/2001.11845 (2020) - [i40]Rajanie Prabha, Manu Tom, Mathias Rothermel, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler:
Lake Ice Monitoring with Webcams and Crowd-Sourced Images. CoRR abs/2002.07875 (2020) - [i39]Ali Athar, Sabarinath Mahadevan, Aljosa Osep, Laura Leal-Taixé, Bastian Leibe:
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos. CoRR abs/2003.08429 (2020) - [i38]Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé:
MOT20: A benchmark for multi object tracking in crowded scenes. CoRR abs/2003.09003 (2020) - [i37]Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé, Jörg Stückler:
Planning from Images with Deep Latent Gaussian Process Dynamics. CoRR abs/2005.03770 (2020) - [i36]Maxim Maximov, Ismail Elezi, Laura Leal-Taixé:
CIAGAN: Conditional Identity Anonymization Generative Adversarial Networks. CoRR abs/2005.09544 (2020) - [i35]Maxim Maximov, Kevin Galim, Laura Leal-Taixé:
Focus on defocus: bridging the synthetic to real domain gap for depth estimation. CoRR abs/2005.09623 (2020) - [i34]Sabarinath Mahadevan, Ali Athar, Aljosa Osep, Sebastian Hennen, Laura Leal-Taixé, Bastian Leibe:
Making a Case for 3D Convolutions for Object Segmentation in Videos. CoRR abs/2008.11516 (2020) - [i33]Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip H. S. Torr, Andreas Geiger, Laura Leal-Taixé, Bastian Leibe:
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking. CoRR abs/2009.07736 (2020) - [i32]Patrick Dendorfer, Aljosa Osep, Laura Leal-Taixé:
Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation. CoRR abs/2010.01114 (2020) - [i31]Patrick Dendorfer, Aljosa Osep, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth, Laura Leal-Taixé:
MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking. CoRR abs/2010.07548 (2020) - [i30]Manu Tom, Rajanie Prabha, Tianyu Wu, Emmanuel Baltsavias, Laura Leal-Taixé, Konrad Schindler:
Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams using Machine Learning. CoRR abs/2010.14300 (2020) - [i29]Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers:
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport. CoRR abs/2010.15261 (2020) - [i28]Tim Meinhardt, Laura Leal-Taixé:
Make One-Shot Video Object Segmentation Efficient Again. CoRR abs/2012.01866 (2020) - [i27]Qunjie Zhou, Torsten Sattler, Laura Leal-Taixé:
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences. CoRR abs/2012.01909 (2020)
2010 – 2019
- 2019
- [j2]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation without Temporal Information. IEEE Trans. Pattern Anal. Mach. Intell. 41(6): 1515-1530 (2019) - [c29]Torsten Sattler, Qunjie Zhou, Marc Pollefeys, Laura Leal-Taixé:
Understanding the Limitations of CNN-Based Absolute Camera Pose Regression. CVPR 2019: 3302-3312 - [c28]Philipp Bergmann, Tim Meinhardt, Laura Leal-Taixé:
Tracking Without Bells and Whistles. ICCV 2019: 941-951 - [c27]Maxim Maximov, Tobias Ritschel, Laura Leal-Taixé, Mario Fritz:
Deep Appearance Maps. ICCV 2019: 8728-8737 - [c26]Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé:
Towards Generalizing Sensorimotor Control Across Weather Conditions. IROS 2019: 4497-4503 - [e7]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part I. Lecture Notes in Computer Science 11129, Springer 2019, ISBN 978-3-030-11008-6 [contents] - [e6]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part II. Lecture Notes in Computer Science 11130, Springer 2019, ISBN 978-3-030-11011-6 [contents] - [e5]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11131, Springer 2019, ISBN 978-3-030-11014-7 [contents] - [e4]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part IV. Lecture Notes in Computer Science 11132, Springer 2019, ISBN 978-3-030-11017-8 [contents] - [e3]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part V. Lecture Notes in Computer Science 11133, Springer 2019, ISBN 978-3-030-11020-8 [contents] - [e2]Laura Leal-Taixé, Stefan Roth:
Computer Vision - ECCV 2018 Workshops - Munich, Germany, September 8-14, 2018, Proceedings, Part VI. Lecture Notes in Computer Science 11134, Springer 2019, ISBN 978-3-030-11023-9 [contents] - [i26]Philipp Bergmann, Tim Meinhardt, Laura Leal-Taixé:
Tracking without bells and whistles. CoRR abs/1903.05625 (2019) - [i25]Torsten Sattler, Qunjie Zhou, Marc Pollefeys, Laura Leal-Taixé:
Understanding the Limitations of CNN-based Absolute Camera Pose Regression. CoRR abs/1903.07504 (2019) - [i24]Patrick Dendorfer, Seyed Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian D. Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixé:
CVPR19 Tracking and Detection Challenge: How crowded can it get? CoRR abs/1906.04567 (2019) - [i23]Qadeer Khan, Patrick Wenzel, Daniel Cremers, Laura Leal-Taixé:
Towards Generalizing Sensorimotor Control Across Weather Conditions. CoRR abs/1907.11025 (2019) - [i22]Qunjie Zhou, Torsten Sattler, Marc Pollefeys, Laura Leal-Taixé:
To Learn or Not to Learn: Visual Localization from Essential Matrices. CoRR abs/1908.01293 (2019) - [i21]Ismail Elezi, Sebastiano Vascon, Alessandro Torcinovich, Marcello Pelillo, Laura Leal-Taixé:
The Group Loss for Deep Metric Learning. CoRR abs/1912.00385 (2019) - [i20]Kishan Sharma, Moritz Gold, Christian Zurbruegg, Laura Leal-Taixé, Jan Dirk Wegner:
HistoNet: Predicting size histograms of object instances. CoRR abs/1912.05227 (2019) - [i19]Guillem Brasó, Laura Leal-Taixé:
Learning a Neural Solver for Multiple Object Tracking. CoRR abs/1912.07515 (2019) - 2018
- [c25]Caner Hazirbas, Sebastian Georg Soyer, Maximilian Christian Staab, Laura Leal-Taixé, Daniel Cremers:
Deep Depth from Focus. ACCV (3) 2018: 525-541 - [c24]Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé:
Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs. CoRL 2018: 253-269 - [c23]Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn:
Fusion of Head and Full-Body Detectors for Multi-Object Tracking. CVPR Workshops 2018: 1428-1437 - [c22]Emanuel Laude, Jan-Hendrik Lange, Jonas Schüpfer, Csaba Domokos, Laura Leal-Taixé, Frank R. Schmidt, Bjoern Andres, Daniel Cremers:
Discrete-Continuous ADMM for Transductive Inference in Higher-Order MRFs. CVPR 2018: 1614-1624 - [c21]Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller:
Lifting Layers: Analysis and Applications. ECCV (1) 2018: 53-68 - [i18]Peter Ochs, Tim Meinhardt, Laura Leal-Taixé, Michael Möller:
Lifting Layers: Analysis and Applications. CoRR abs/1803.08660 (2018) - [i17]Seyed Hamid Rezatofighi, Roman Kaskman, Farbod T. Motlagh, Qinfeng Shi, Daniel Cremers, Laura Leal-Taixé, Ian D. Reid:
Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks. CoRR abs/1805.00613 (2018) - [i16]Patrick Wenzel, Qadeer Khan, Daniel Cremers, Laura Leal-Taixé:
Modular Vehicle Control for Transferring Semantic Information to Unseen Weather Conditions using GANs. CoRR abs/1807.01001 (2018) - [i15]Mengyu Chu, You Xie, Laura Leal-Taixé, Nils Thuerey:
Temporally Coherent GANs for Video Super-Resolution (TecoGAN). CoRR abs/1811.09393 (2018) - 2017
- [c20]Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
One-Shot Video Object Segmentation. CVPR 2017: 5320-5329 - [c19]Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers:
Image-Based Localization Using LSTMs for Structured Feature Correlation. ICCV 2017: 627-637 - [i14]Caner Hazirbas, Laura Leal-Taixé, Daniel Cremers:
Deep Depth From Focus. CoRR abs/1704.01085 (2017) - [i13]Laura Leal-Taixé, Anton Milan, Konrad Schindler, Daniel Cremers, Ian D. Reid, Stefan Roth:
Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking. CoRR abs/1704.02781 (2017) - [i12]Roberto Henschel, Laura Leal-Taixé, Daniel Cremers, Bodo Rosenhahn:
Improvements to Frank-Wolfe optimization for multi-detector multi-object tracking. CoRR abs/1705.08314 (2017) - [i11]Dário Augusto Borges Oliveira, Laura Leal-Taixé, Raul Queiroz Feitosa, Bodo Rosenhahn:
Automatic tracking of vessel-like structures from a single starting point. CoRR abs/1706.02434 (2017) - [i10]Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
Video Object Segmentation Without Temporal Information. CoRR abs/1709.06031 (2017) - [i9]Daniel Cremers, Laura Leal-Taixé, René Vidal:
Deep Learning for Computer Vision (Dagstuhl Seminar 17391). Dagstuhl Reports 7(9): 109-125 (2017) - 2016
- [j1]Dário Augusto Borges Oliveira, Laura Leal-Taixé, Raul Queiroz Feitosa, Bodo Rosenhahn:
Automatic tracking of vessel-like structures from a single starting point. Comput. Medical Imaging Graph. 47: 1-15 (2016) - [c18]Laura Leal-Taixé, Cristian Canton-Ferrer, Konrad Schindler:
Learning by Tracking: Siamese CNN for Robust Target Association. CVPR Workshops 2016: 418-425 - [i8]Anton Milan, Laura Leal-Taixé, Ian D. Reid, Stefan Roth, Konrad Schindler:
MOT16: A Benchmark for Multi-Object Tracking. CoRR abs/1603.00831 (2016) - [i7]Laura Leal-Taixé, Cristian Canton-Ferrer, Konrad Schindler:
Learning by tracking: Siamese CNN for robust target association. CoRR abs/1604.07866 (2016) - [i6]Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn, Konrad Schindler:
Tracking with multi-level features. CoRR abs/1607.07304 (2016) - [i5]Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc Van Gool:
One-Shot Video Object Segmentation. CoRR abs/1611.05198 (2016) - [i4]Florian Walch, Caner Hazirbas, Laura Leal-Taixé, Torsten Sattler, Sebastian Hilsenbeck, Daniel Cremers:
Image-based Localization with Spatial LSTMs. CoRR abs/1611.07890 (2016) - 2015
- [c17]Anton Milan, Laura Leal-Taixé, Konrad Schindler, Ian D. Reid:
Joint tracking and segmentation of multiple targets. CVPR 2015: 5397-5406 - [c16]Michele Fenzi, Laura Leal-Taixé, Jörn Ostermann, Tinne Tuytelaars:
Continuous Pose Estimation with a Spatial Ensemble of Fisher Regressors. ICCV 2015: 1035-1043 - [c15]Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn:
Solving Multiple People Tracking in a Minimum Cost Arborescence. WACV Workshops 2015: 71-72 - [c14]Michele Fenzi, Laura Leal-Taixé, Konrad Schindler, Jörn Ostermann:
Pose Estimation of Object Categories in Videos Using Linear Programming. WACV 2015: 821-828 - [i3]Laura Leal-Taixé, Anton Milan, Ian D. Reid, Stefan Roth, Konrad Schindler:
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking. CoRR abs/1504.01942 (2015) - [i2]Jiri Matas, Vittorio Murino, Bodo Rosenhahn, Laura Leal-Taixé:
Holistic Scene Understanding (Dagstuhl Seminar 15081). Dagstuhl Reports 5(2): 80-108 (2015) - 2014
- [b1]Laura Leal-Taixé:
Multiple object tracking with context awareness. University of Hanover, 2014 - [c13]Laura Leal-Taixé, Michele Fenzi, Alina Kuznetsova, Bodo Rosenhahn, Silvio Savarese:
Learning an Image-Based Motion Context for Multiple People Tracking. CVPR 2014: 3542-3549 - [c12]Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn:
Efficient Multiple People Tracking Using Minimum Cost Arborescences. GCPR 2014: 265-276 - [i1]Laura Leal-Taixé:
Multiple object tracking with context awareness. CoRR abs/1411.7935 (2014) - 2013
- [c11]Michele Fenzi, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann:
Class Generative Models Based on Feature Regression for Pose Estimation of Object Categories. CVPR 2013: 755-762 - [c10]Alina Kuznetsova, Laura Leal-Taixé, Bodo Rosenhahn:
Real-Time Sign Language Recognition Using a Consumer Depth Camera. ICCV Workshops 2013: 83-90 - [p1]Laura Leal-Taixé, Bodo Rosenhahn:
Pedestrian Interaction in Tracking: The Social Force Model and Global Optimization Methods. Modeling, Simulation and Visual Analysis of Crowds 2013: 267-294 - 2012
- [c9]Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn:
Branch-and-price global optimization for multi-view multi-target tracking. CVPR 2012: 1987-1994 - [c8]Michele Fenzi, Ralf Dragon, Laura Leal-Taixé, Bodo Rosenhahn, Jörn Ostermann:
3D Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized RANSAC and Model Updating. DAGM/OAGM Symposium 2012: 123-133 - [e1]Frank Dellaert, Jan-Michael Frahm, Marc Pollefeys, Laura Leal-Taixé, Bodo Rosenhahn:
Outdoor and Large-Scale Real-World Scene Analysis - 15th International Workshop on Theoretical Foundations of Computer Vision, Dagstuhl Castle, Germany, June 26 - July 1, 2011. Revised Selected Papers. Lecture Notes in Computer Science 7474, Springer 2012, ISBN 978-3-642-34090-1 [contents] - 2011
- [c7]Gerard Pons-Moll, Laura Leal-Taixé, Tri Truong, Bodo Rosenhahn:
Efficient and Robust Shape Matching for Model Based Human Motion Capture. DAGM-Symposium 2011: 416-425 - [c6]Gerard Pons-Moll, Andreas Baak, Juergen Gall, Laura Leal-Taixé, Meinard Müller, Hans-Peter Seidel, Bodo Rosenhahn:
Outdoor human motion capture using inverse kinematics and von mises-fisher sampling. ICCV 2011: 1243-1250 - [c5]Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn:
Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker. ICCV Workshops 2011: 120-127 - [c4]Laura Leal-Taixé, Gerard Pons-Moll, Bodo Rosenhahn:
Exploiting Pedestrian Interaction via Global Optimization and Social Behaviors. Theoretical Foundations of Computer Vision 2011: 1-26 - [c3]Gerard Pons-Moll, Laura Leal-Taixé, Juergen Gall, Bodo Rosenhahn:
Data-Driven Manifolds for Outdoor Motion Capture. Theoretical Foundations of Computer Vision 2011: 305-328 - 2010
- [c2]Laura Leal-Taixé, Matthias Heydt, Sebastian Weiße, Axel Rosenhahn, Bodo Rosenhahn:
Classification of Swimming Microorganisms Motion Patterns in 4D Digital In-Line Holography Data. DAGM-Symposium 2010: 283-292 - [c1]Laura Leal-Taixé, Matthias Heydt, Axel Rosenhahn, Bodo Rosenhahn:
Understanding What we Cannot See: Automatic Analysis of 4D Digital In-Line Holographic Microscopy Data. Video Processing and Computational Video 2010: 52-76
Coauthor Index
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