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ORCIDNico Messikommer
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2020 – today
- 2024
[c7]Nico Messikommer
, Giovanni Cioffi, Mathias Gehrig, Davide Scaramuzza:
Reinforcement Learning Meets Visual Odometry. ECCV (59) 2024: 76-92- [c6]Nico Messikommer, Yunlong Song, Davide Scaramuzza:
Contrastive Initial State Buffer for Reinforcement Learning. ICRA 2024: 2866-2872 - [c5]Yifei Liu, Mathias Gehrig, Nico Messikommer, Marco Cannici, Davide Scaramuzza:
Revisiting Token Pruning for Object Detection and Instance Segmentation. WACV 2024: 2646-2656 - [i13]Nico Messikommer, Giovanni Cioffi, Mathias Gehrig, Davide Scaramuzza:
Reinforcement Learning Meets Visual Odometry. CoRR abs/2407.15626 (2024) - [i12]Taylan Soydan, Nikola Zubic, Nico Messikommer, Siddhartha Mishra, Davide Scaramuzza:
S7: Selective and Simplified State Space Layers for Sequence Modeling. CoRR abs/2410.03464 (2024) - [i11]Hongze Wang, Jiaxu Xing, Nico Messikommer, Davide Scaramuzza:
Environment as Policy: Learning to Race in Unseen Tracks. CoRR abs/2410.22308 (2024) - 2023
- [c4]Nico Messikommer, Carter Fang, Mathias Gehrig, Davide Scaramuzza:
Data-Driven Feature Tracking for Event Cameras. CVPR 2023: 5642-5651 - [i10]Yifei Liu, Mathias Gehrig, Nico Messikommer, Marco Cannici, Davide Scaramuzza:
Revisiting Token Pruning for Object Detection and Instance Segmentation. CoRR abs/2306.07050 (2023) - [i9]Rong Zou, Manasi Muglikar, Nico Messikommer, Davide Scaramuzza:
Seeing Behind Dynamic Occlusions with Event Cameras. CoRR abs/2307.15829 (2023) - [i8]Nico Messikommer, Yunlong Song, Davide Scaramuzza:
Contrastive Initial State Buffer for Reinforcement Learning. CoRR abs/2309.09752 (2023) - 2022
- [j1]Nico Messikommer, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
Bridging the Gap Between Events and Frames Through Unsupervised Domain Adaptation. IEEE Robotics Autom. Lett. 7(2): 3515-3522 (2022) - [c3]Nico Messikommer, Stamatios Georgoulis, Daniel Gehrig, Stepan Tulyakov, Julius Erbach, Alfredo Bochicchio, Yuanyou Li, Davide Scaramuzza:
Multi-Bracket High Dynamic Range Imaging with Event Cameras. CVPR Workshops 2022: 546-556 - [c2]Zhaoning Sun, Nico Messikommer, Daniel Gehrig, Davide Scaramuzza:
ESS: Learning Event-Based Semantic Segmentation from Still Images. ECCV (34) 2022: 341-357 - [i7]Nico Messikommer, Stamatios Georgoulis, Daniel Gehrig, Stepan Tulyakov, Julius Erbach, Alfredo Bochicchio, Yuanyou Li, Davide Scaramuzza:
Multi-Bracket High Dynamic Range Imaging with Event Cameras. CoRR abs/2203.06622 (2022) - [i6]Zhaoning Sun, Nico Messikommer, Daniel Gehrig, Davide Scaramuzza:
ESS: Learning Event-based Semantic Segmentation from Still Images. CoRR abs/2203.10016 (2022) - [i5]Nico Messikommer, Carter Fang, Mathias Gehrig, Davide Scaramuzza:
Data-driven Feature Tracking for Event Cameras. CoRR abs/2211.12826 (2022) - 2021
- [i4]Nico Messikommer, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation. CoRR abs/2109.02618 (2021) - 2020
- [c1]Nico Messikommer, Daniel Gehrig, Antonio Loquercio, Davide Scaramuzza:
Event-Based Asynchronous Sparse Convolutional Networks. ECCV (8) 2020: 415-431 - [i3]Nico Messikommer, Daniel Gehrig, Antonio Loquercio, Davide Scaramuzza:
Event-based Asynchronous Sparse Convolutional Networks. CoRR abs/2003.09148 (2020)
2010 – 2019
- 2017
- [i2]Niklas Funk, Nikhilesh Alatur, Robin Deuber, Frederick Gonon, Nico Messikommer, Julian Nubert, Moritz Patriarca, Simon Schaefer, Dominic Scotoni, Nicholas Bünger, Renaud Dubé, Raghav Khanna, Mark Pfeiffer, Erik Wilhelm, Roland Siegwart:
Autonomous Electric Race Car Design. CoRR abs/1711.00548 (2017) - [i1]Nico Messikommer, Simon Schaefer, Renaud Dubé, Mark Pfeiffer:
Cone Detection using a Combination of LiDAR and Vision-based Machine Learning. CoRR abs/1711.02079 (2017)
Coauthor Index
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