Zobrazeno 1 - 10
of 133
pro vyhledávání: '"Zimmer, Walter"'
Autor:
Mohamed, Sondos, Zimmer, Walter, Greer, Ross, Ghita, Ahmed Alaaeldin, Castrillón-Santana, Modesto, Trivedi, Mohan, Knoll, Alois, Carta, Salvatore Mario, Marras, Mirko
Accurately detecting 3D objects from monocular images in dynamic roadside scenarios remains a challenging problem due to varying camera perspectives and unpredictable scene conditions. This paper introduces a two-stage training strategy to address th
Externí odkaz:
http://arxiv.org/abs/2408.15637
Autor:
Zhou, Xingcheng, Fu, Deyu, Zimmer, Walter, Liu, Mingyu, Lakshminarasimhan, Venkatnarayanan, Strand, Leah, Knoll, Alois C.
Existing roadside perception systems are limited by the absence of publicly available, large-scale, high-quality 3D datasets. Exploring the use of cost-effective, extensive synthetic datasets offers a viable solution to tackle this challenge and enha
Externí odkaz:
http://arxiv.org/abs/2407.20818
Autor:
Liu, Mingyu, Yurtsever, Ekim, Brede, Marc, Meng, Jun, Zimmer, Walter, Zhou, Xingcheng, Zagar, Bare Luka, Cui, Yuning, Knoll, Alois
Accurate and effective 3D object detection is critical for ensuring the driving safety of autonomous vehicles. Recently, state-of-the-art two-stage 3D object detectors have exhibited promising performance. However, these methods refine proposals indi
Externí odkaz:
http://arxiv.org/abs/2405.06782
In the context of Intelligent Transportation Systems (ITS), efficient data compression is crucial for managing large-scale point cloud data acquired by roadside LiDAR sensors. The demand for efficient storage, streaming, and real-time object detectio
Externí odkaz:
http://arxiv.org/abs/2405.01750
Autor:
Zimmer, Walter, Wardana, Gerhard Arya, Sritharan, Suren, Zhou, Xingcheng, Song, Rui, Knoll, Alois C.
Cooperative perception offers several benefits for enhancing the capabilities of autonomous vehicles and improving road safety. Using roadside sensors in addition to onboard sensors increases reliability and extends the sensor range. External sensors
Externí odkaz:
http://arxiv.org/abs/2403.01316
Autor:
Song, Rui, Liang, Chenwei, Cao, Hu, Yan, Zhiran, Zimmer, Walter, Gross, Markus, Festag, Andreas, Knoll, Alois
Collaborative perception in automated vehicles leverages the exchange of information between agents, aiming to elevate perception results. Previous camera-based collaborative 3D perception methods typically employ 3D bounding boxes or bird's eye view
Externí odkaz:
http://arxiv.org/abs/2402.07635
Autor:
Ghita, Ahmed, Antoniussen, Bjørk, Zimmer, Walter, Greer, Ross, Creß, Christian, Møgelmose, Andreas, Trivedi, Mohan M., Knoll, Alois C.
The curation of large-scale datasets is still costly and requires much time and resources. Data is often manually labeled, and the challenge of creating high-quality datasets remains. In this work, we fill the research gap using active learning for m
Externí odkaz:
http://arxiv.org/abs/2402.03235
Autor:
Creß, Christian, Zimmer, Walter, Purschke, Nils, Doan, Bach Ngoc, Kirchner, Sven, Lakshminarasimhan, Venkatnarayanan, Strand, Leah, Knoll, Alois C.
Event-based cameras are predestined for Intelligent Transportation Systems (ITS). They provide very high temporal resolution and dynamic range, which can eliminate motion blur and improve detection performance at night. However, event-based images la
Externí odkaz:
http://arxiv.org/abs/2401.08474
Autor:
Liu, Mingyu, Yurtsever, Ekim, Fossaert, Jonathan, Zhou, Xingcheng, Zimmer, Walter, Cui, Yuning, Zagar, Bare Luka, Knoll, Alois C.
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for developing reliable autonomous driving algorithms. Previous dataset su
Externí odkaz:
http://arxiv.org/abs/2401.01454
Point cloud registration is challenging in the presence of heavy outlier correspondences. This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice. The gravity directions a
Externí odkaz:
http://arxiv.org/abs/2311.01432