2023 - Research.com Computer Science in Germany Leader Award
2022 - Research.com Computer Science in Germany Leader Award
2021 - German National Academy of Sciences Leopoldina - Deutsche Akademie der Naturforscher Leopoldina – Nationale Akademie der Wissenschaften Informatics
2018 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to large-scale object recognition, human detection and pose estimation
2017 - IEEE Fellow For contributions to large-scale object recognition, human detection and pose estimation
His main research concerns Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Object detection. His Artificial intelligence research integrates issues from Pedestrian detection and Natural language processing. Bernt Schiele has researched Computer vision in several fields, including Probabilistic logic, Robustness and Pattern recognition.
His Machine learning research focuses on subjects like Benchmark, which are linked to Video tracking. His Pattern recognition research is multidisciplinary, relying on both Object, Minimum bounding box, Histogram and 3D single-object recognition. Sliding window protocol is closely connected to Pascal in his research, which is encompassed under the umbrella topic of Object detection.
Bernt Schiele mainly focuses on Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Object. His research in Object detection, Segmentation, Image, Pose and Training set are components of Artificial intelligence. Bernt Schiele combines subjects such as Pedestrian detection, Detector and Robustness with his study of Computer vision.
His Machine learning research incorporates elements of Key, Task and Benchmark. His Pattern recognition research is multidisciplinary, incorporating perspectives in Contextual image classification and Histogram. Bernt Schiele focuses mostly in the field of Activity recognition, narrowing it down to topics relating to Wearable computer and, in certain cases, Multimedia and Human–computer interaction.
Bernt Schiele mostly deals with Artificial intelligence, Machine learning, Pattern recognition, Robustness and Training set. All of his Artificial intelligence and Deep learning, Segmentation, Contextual image classification, Image and Leverage investigations are sub-components of the entire Artificial intelligence study. His work focuses on many connections between Leverage and other disciplines, such as Depth perception, that overlap with his field of interest in Computer vision.
Many of his research projects under Computer vision are closely connected to Decomposition with Decomposition, tying the diverse disciplines of science together. His Machine learning research incorporates themes from Adversarial system, Task, State, Benchmark and Shot. The concepts of his Pattern recognition study are interwoven with issues in Image quality, Real image and Feature.
Bernt Schiele mainly investigates Artificial intelligence, Machine learning, Training set, Robustness and Deep learning. His Artificial intelligence research includes elements of Task and Pattern recognition. His study in the field of Incremental learning also crosses realms of Training, Class and Representativeness heuristic.
His Training set research also works with subjects such as
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The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts;Mohamed Omran;Sebastian Ramos;Timo Rehfeld.
computer vision and pattern recognition (2016)
Pedestrian Detection: An Evaluation of the State of the Art
P. Dollar;C. Wojek;B. Schiele;P. Perona.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
Generative adversarial text to image synthesis
Scott Reed;Zeynep Akata;Xinchen Yan;Lajanugen Logeswaran.
international conference on machine learning (2016)
2D Human Pose Estimation: New Benchmark and State of the Art Analysis
Mykhaylo Andriluka;Leonid Pishchulin;Peter Gehler;Bernt Schiele.
computer vision and pattern recognition (2014)
Pedestrian detection: A benchmark
Piotr Dollar;Christian Wojek;Bernt Schiele;Pietro Perona.
computer vision and pattern recognition (2009)
A tutorial on human activity recognition using body-worn inertial sensors
Andreas Bulling;Ulf Blanke;Bernt Schiele.
ACM Computing Surveys (2014)
Robust Object Detection with Interleaved Categorization and Segmentation
Bastian Leibe;Aleš Leonardis;Bernt Schiele.
International Journal of Computer Vision (2008)
Combined Object Categorization and Segmentation With an Implicit Shape Model
Bastian Leibe;Ales Leonardis;Bernt Schiele.
Workshop on Statistical Learning in Computer Vision, Prague, Czech Republic, 2004 (2004)
People-tracking-by-detection and people-detection-by-tracking
M. Andriluka;S. Roth;B. Schiele.
computer vision and pattern recognition (2008)
Pedestrian detection in crowded scenes
B. Leibe;E. Seemann;B. Schiele.
computer vision and pattern recognition (2005)
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