Članki z zahtevami za javni dostop - Philipp KrähenbühlVeč o tem
Na voljo nekje: 22
Context encoders: Feature learning by inpainting
D Pathak, P Krahenbuhl, J Donahue, T Darrell, AA Efros
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Zahteve: US National Science Foundation
Center-based 3d object detection and tracking
T Yin, X Zhou, P Krähenbühl
CVPR, 2021
Zahteve: US National Science Foundation
Tracking Objects as Points
X Zhou, V Koltun, P Krähenbühl
ECCV, 2020
Zahteve: US National Science Foundation
Detecting twenty-thousand classes using image-level supervision
X Zhou, R Girdhar, A Joulin, P Krähenbühl, I Misra
European conference on computer vision, 350-368, 2022
Zahteve: US National Science Foundation
Learning by cheating
D Chen, B Zhou, V Koltun, P Krähenbühl
Conference on Robot Learning, 66-75, 2019
Zahteve: US National Science Foundation
Learning dense correspondence via 3d-guided cycle consistency
T Zhou, P Krahenbuhl, M Aubry, Q Huang, AA Efros
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Zahteve: US National Science Foundation
Cross-view transformers for real-time map-view semantic segmentation
B Zhou, P Krähenbühl
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Zahteve: US National Science Foundation
Multimodal virtual point 3d detection
T Yin, X Zhou, P Krähenbühl
Advances in Neural Information Processing Systems 34, 16494-16507, 2021
Zahteve: US National Science Foundation
Learning from all vehicles
D Chen, P Krähenbühl
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Zahteve: US National Science Foundation
Global tracking transformers
X Zhou, T Yin, V Koltun, P Krähenbühl
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Zahteve: US National Science Foundation
Learning video representations from large language models
Y Zhao, I Misra, P Krähenbühl, R Girdhar
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
Zahteve: US National Science Foundation
Towards long-form video understanding
CY Wu, P Krahenbuhl
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Zahteve: US National Science Foundation
Simple multi-dataset detection
X Zhou, V Koltun, P Krähenbühl
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Zahteve: US National Science Foundation
Learning to drive from a world on rails
D Chen, V Koltun, P Krähenbühl
ICCV 2021, 2021
Zahteve: US National Science Foundation
A multigrid method for efficiently training video models
CY Wu, R Girshick, K He, C Feichtenhofer, P Krahenbuhl
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Zahteve: US National Science Foundation
Real-time online video detection with temporal smoothing transformers
Y Zhao, P Krähenbühl
European Conference on Computer Vision, 485-502, 2022
Zahteve: US National Science Foundation
Long-tail detection with effective class-margins
J Hyun Cho, P Krähenbühl
European Conference on Computer Vision, 698-714, 2022
Zahteve: US National Science Foundation
Predicting a protein's stability under a million mutations
J Ouyang-Zhang, D Diaz, A Klivans, P Krähenbühl
Advances in Neural Information Processing Systems 36, 76229-76247, 2023
Zahteve: US National Science Foundation
Distilling vision-language models on millions of videos
Y Zhao, L Zhao, X Zhou, J Wu, CT Chu, H Miao, F Schroff, H Adam, T Liu, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Zahteve: US National Science Foundation
Domain Adaptation Through Task Distillation
B Zhou, N Kalra, P Krähenbühl
ECCV, 2020
Zahteve: US National Science Foundation
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