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Timo Lüddecke
Timo Lüddecke
University of Göttingen and Campus Institute Data Science (CIDAS)
Bestätigte E-Mail-Adresse bei uni-goettingen.de
Titel
Zitiert von
Zitiert von
Jahr
Image segmentation using text and image prompts
T Lüddecke, A Ecker
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
251*2022
Learning to segment affordances
T Lüddecke, F Wörgötter
Proceedings of the IEEE International Conference on Computer Vision …, 2017
312017
Attention on abstract visual reasoning
L Hahne, T Lüddecke, F Wörgötter, D Kappel
arXiv preprint arXiv:1911.05990, 2019
232019
Context-based affordance segmentation from 2D images for robot actions
T Lüddecke, T Kulvicius, F Wörgötter
Robotics and Autonomous Systems 119, 92-107, 2019
222019
GPT4GEO: How a Language Model Sees the World's Geography
J Roberts, T Lüddecke, S Das, K Han, S Albanie
arXiv preprint arXiv:2306.00020, 2023
152023
Distributional semantics of objects in visual scenes in comparison to text
T Lüddecke, A Agostini, M Fauth, M Tamosiunaite, F Wörgötter
Artificial Intelligence 274, 44-65, 2019
152019
Deep metadata fusion for traffic light to lane assignment
T Langenberg, T Lüddecke, F Wörgötter
IEEE Robotics and Automation Letters 4 (2), 973-980, 2019
82019
One-shot multi-path planning using fully convolutional networks in a comparison to other algorithms
T Kulvicius, S Herzog, T Lüddecke, M Tamosiunaite, F Wörgötter
Frontiers in Neurorobotics 14, 600984, 2021
72021
Self-supervised representation learning of neuronal morphologies
MA Weis, L Pede, T Lüddecke, AS Ecker
Transactions on Machine Learning Research, 2023
6*2023
One-shot multi-path planning for robotic applications using fully convolutional networks
T Kulvicius, S Herzog, T Lüddecke, M Tamosiunaite, F Wörgötter
2020 IEEE International Conference on Robotics and Automation (ICRA), 1460-1466, 2020
62020
One-shot path planning for multi-agent systems using fully convolutional neural network
T Kulvicius, S Herzog, T Lüddecke, M Tamosiunaite, F Wörgötter
arXiv preprint arXiv:2004.00568, 2020
62020
Large-scale unsupervised discovery of excitatory morphological cell types in mouse visual cortex
MA Weis, S Papadopoulos, L Hansel, T Lüddecke, B Celii, PG Fahey, ...
bioRxiv, 2022.12. 22.521541, 2022
52022
The role of data for one-shot semantic segmentation
T Luddecke, A Ecker
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
52021
Charting new territories: Exploring the geographic and geospatial capabilities of multimodal llms
J Roberts, T Lüddecke, R Sheikh, K Han, S Albanie
arXiv preprint arXiv:2311.14656, 2023
32023
Fine-grained action plausibility rating
T Lueddecke, F Woergoetter
Robotics and Autonomous Systems 129, 103511, 2020
32020
Convolutional neural networks for movement prediction in videos
A Warnecke, T Lüddecke, F Wörgötter
Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland …, 2017
32017
Vibroacoustic Frequency Response Prediction with Query-based Operator Networks
J van Delden, J Schultz, C Blech, SC Langer, T Lüddecke
arXiv preprint arXiv:2310.05469, 2023
12023
3D Object Classification via Part Graphs.
F Teich, T Lüddecke, F Wörgötter
VISIGRAPP (5: VISAPP), 417-426, 2021
12021
Learning to label affordances from simulated and real data
T Lüddecke, F Wörgötter
arXiv preprint arXiv:1709.08872, 2017
12017
Part-driven visual perception of 3D objects
F Gressmann, T Lüddecke, T Ivanovska, M Schoeler, F Wörgötter
International Conference on Computer Vision Theory and Applications 6, 370-377, 2017
12017
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