no code implementations • 10 May 2024 • MingYu Liu, Ekim Yurtsever, Marc Brede, Jun Meng, Walter Zimmer, Xingcheng Zhou, Bare Luka Zagar, Yuning Cui, Alois Knoll
In this study, we introduce an object relation module, consisting of a graph generator and a graph neural network (GNN), to learn the spatial information from certain patterns to improve 3D object detection.
2 code implementations • 2 May 2024 • Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, QIngwei Lin, Ming Jin, Alois Knoll
Ensuring the safety of Reinforcement Learning (RL) is crucial for its deployment in real-world applications.
no code implementations • 8 Apr 2024 • Liguo Zhou, Yirui Zhou, Huaming Liu, Alois Knoll
Our findings highlight the potential of Residual Chain Loss to revolutionize planning component of autonomous driving systems, marking a significant step forward in the quest for level 5 autonomous driving system.
no code implementations • 8 Apr 2024 • Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda, Vahid Zolfaghari, Sven Kirchner, Nils Purschke, Muhammad Aqib Khan, Viktor Vorobev, Alois Knoll
We present a prototype of a tool leveraging the synergy of model driven engineering (MDE) and Large Language Models (LLM) for the purpose of software development process automation in the automotive industry.
1 code implementation • Proceedings of the AAAI Conference on Artificial Intelligence 2024 • Yuning Cui, Wenqi Ren, Alois Knoll
Extensive experiments demonstrate that our network achieves state-of-the-art performance on 11 benchmark datasets for three representative image restoration tasks, including image dehazing, image desnowing, and image defocus deblurring.
Ranked #8 on Image Dehazing on SOTS Outdoor
no code implementations • 21 Mar 2024 • Krzysztof Lebioda, Viktor Vorobev, Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari, Alois Knoll
We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined.
1 code implementation • 21 Mar 2024 • Yuning Cui, Syed Waqas Zamir, Salman Khan, Alois Knoll, Mubarak Shah, Fahad Shahbaz Khan
Our approach is motivated by the observation that different degradation types impact the image content on different frequency subbands, thereby requiring different treatments for each restoration task.
no code implementations • 20 Mar 2024 • Brian Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen, Alois Knoll
This paper presents safety-oriented object detection via a novel Ego-Centric Intersection-over-Union (EC-IoU) measure, addressing practical concerns when applying state-of-the-art learning-based perception models in safety-critical domains such as autonomous driving.
no code implementations • 13 Mar 2024 • Shangding Gu, Alois Knoll, Ming Jin
The development of Large Language Models (LLMs) often confronts challenges stemming from the heavy reliance on human annotators in the reinforcement learning with human feedback (RLHF) framework, or the frequent and costly external queries tied to the self-instruct paradigm.
1 code implementation • 7 Mar 2024 • Boyang Peng, Sanqing Qu, Yong Wu, Tianpei Zou, Lianghua He, Alois Knoll, Guang Chen, Changjun Jiang
In this paper, we target a practical setting where only a well-trained source model is available and investigate how we can realize IP protection.
2 code implementations • 6 Mar 2024 • Sanqing Qu, Tianpei Zou, Lianghua He, Florian Röhrbein, Alois Knoll, Guang Chen, Changjun Jiang
Besides, LEAD is also appealing in that it is complementary to most existing methods.
Ranked #1 on Universal Domain Adaptation on VisDA2017
1 code implementation • Neural Networks 2024 • Yuning Cui, Alois Knoll
In this paper, we develop a dual-domain strip attention mechanism for image restoration by enhancing representation learning, which consists of spatial and frequency strip attention units.
Ranked #5 on Image Dehazing on SOTS Outdoor
no code implementations • 29 Feb 2024 • Yu Zhang, long wen, Xiangtong Yao, Zhenshan Bing, Linghuan Kong, wei he, Alois Knoll
Subsequently, the hyperparameters of the Gaussian model are trained with a specially compound kernel, and the Gaussian model's online inferential capability and computational efficiency are strengthened by updating a solitary inducing point derived from new samples, in conjunction with the learned hyperparameters.
no code implementations • 29 Feb 2024 • Haotian Liu, Sanqing Qu, Fan Lu, Zongtao Bu, Florian Roehrbein, Alois Knoll, Guang Chen
Therefore, existing complementary learning approaches for MDE fuse intensity information from images and scene details from event data for better scene understanding.
no code implementations • 26 Feb 2024 • Yu Zhang, Guangyao Tian, long wen, Xiangtong Yao, Liding Zhang, Zhenshan Bing, wei he, Alois Knoll
This paper proposes a LiDAR-based goal-seeking and exploration framework, addressing the efficiency of online obstacle avoidance in unstructured environments populated with static and moving obstacles.
no code implementations • 22 Feb 2024 • Yanliang Huang, Liguo Zhou, Chang Liu, Alois Knoll
The implementation of Autonomous Driving (AD) technologies within urban environments presents significant challenges.
no code implementations • 12 Feb 2024 • Rui Song, Chenwei Liang, Hu Cao, Zhiran Yan, Walter Zimmer, Markus Gross, Andreas Festag, Alois Knoll
Additionally, due to the lack of a collaborative perception dataset designed for semantic occupancy prediction, we augment a current collaborative perception dataset to include 3D collaborative semantic occupancy labels for a more robust evaluation.
no code implementations • 9 Feb 2024 • Fengyi Shen, Li Zhou, Kagan Kucukaytekin, Ziyuan Liu, He Wang, Alois Knoll
Data generation is recognized as a potent strategy for unsupervised domain adaptation (UDA) pertaining semantic segmentation in adverse weathers.
1 code implementation • 28 Jan 2024 • Liguo Zhou, Yinglei Song, Yichao Gao, Zhou Yu, Michael Sodamin, Hongshen Liu, Liang Ma, Lian Liu, Hao liu, Yang Liu, Haichuan Li, Guang Chen, Alois Knoll
However, the availability of free and open-source simulators is limited, and the installation and configuration process can be daunting for beginners and interdisciplinary researchers.
1 code implementation • Knowledge-Based Systems 2023 • Yuning Cui, Alois Knoll
Image restoration aims to reconstruct a clear image from a degraded observation.
Ranked #1 on Image Dehazing on SOTS Outdoor
no code implementations • 5 Dec 2023 • Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll
Multi-goal robot manipulation tasks with sparse rewards are difficult for reinforcement learning (RL) algorithms due to the inefficiency in collecting successful experiences.
no code implementations • 4 Dec 2023 • Christoph Hümmer, Manuel Schwonberg, Liangwei Zhou, Hu Cao, Alois Knoll, Hanno Gottschalk
We thus propose a new vision-language approach for domain generalized segmentation, which improves the domain generalization SOTA by 7. 6% mIoU when training on the synthetic GTA5 dataset.
Ranked #1 on Semantic Segmentation on Cityscapes test (using extra training data)
no code implementations • 20 Nov 2023 • Habtom Kahsay Gidey, Peter Hillmann, Andreas Karcher, Alois Knoll
In this survey, we aim to explore the role of cognitive architectures in supporting efforts towards engineering software bots with advanced general intelligence.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2023 • Yuning Cui, Wenqi Ren, Xiaochun Cao, Alois Knoll
Image restoration aims to reconstruct the latent sharp image from its corrupted counterpart.
Ranked #2 on Image Dehazing on SOTS Outdoor
no code implementations • 2 Nov 2023 • Xinyi Li, Zijian Ma, Yinlong Liu, Walter Zimmer, Hu Cao, Feihu Zhang, Alois Knoll
This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice.
no code implementations • 26 Oct 2023 • Chang Liu, Liguo Zhou, Yanliang Huang, Alois Knoll
Vehicle perception systems strive to achieve comprehensive and rapid visual interpretation of their surroundings for improved safety and navigation.
no code implementations • 3 Oct 2023 • Javier Lopez-Randulfe, Nico Reeb, Alois Knoll
Thus, we provide an end-to-end neuromorphic application that generates the frequency spectrum of an electric signal without the need for an ADC or a digital signal processing algorithm.
no code implementations • 21 Sep 2023 • Panagiotis Petropoulakis, Ludwig Gräf, Josip Josifovski, Mohammadhossein Malmir, Alois Knoll
The results show that RL agents using numerical states can perform on par with non-learning baselines.
no code implementations • 14 Sep 2023 • Syed Sha Qutub, Neslihan Kose, Rafael Rosales, Michael Paulitsch, Korbinian Hagn, Florian Geissler, Yang Peng, Gereon Hinz, Alois Knoll
The proposed loss functions in BEA improve the confidence score calibration and lower the uncertainty error, which results in a better distinction of true and false positives and, eventually, higher accuracy of the object detection models.
no code implementations • 22 Aug 2023 • Soubarna Banik, Edvard Avagyan, Sayantan Auddy, Alejandro Mendoza Gracia, Alois Knoll
Existing skeleton-based 3D human pose estimation methods only predict joint positions.
1 code implementation • IJCAI 2023 • Yuning Cui, Yi Tao, Luoxi Jing, Alois Knoll
As a long-standing task, image restoration aims to recover the latent sharp image from its degraded counterpart.
Ranked #6 on Image Dehazing on SOTS Outdoor
no code implementations • 15 Jun 2023 • Mohammadhossein Malmir, Josip Josifovski, Noah Klarmann, Alois Knoll
We introduce a disturbance-augmented Markov decision process in delayed settings as a novel representation to incorporate disturbance estimation in training on-policy reinforcement learning algorithms.
no code implementations • 30 May 2023 • Hongkuan Zhou, Zhenshan Bing, Xiangtong Yao, Xiaojie Su, Chenguang Yang, Kai Huang, Alois Knoll
In this evaluation, we set up ten tasks and achieved an average 30% improvement in our approach compared to the current state-of-the-art approach, demonstrating a high generalization capability in both simulated environments and the real world.
no code implementations • 26 May 2023 • Habtom Kahsay Gidey, Peter Hillmann, Andreas Karcher, Alois Knoll
Software bots operating in multiple virtual digital platforms must understand the platforms' affordances and behave like human users.
1 code implementation • 23 May 2023 • Zhenshan Bing, Yuan Meng, Yuqi Yun, Hang Su, Xiaojie Su, Kai Huang, Alois Knoll
Generative model-based deep clustering frameworks excel in classifying complex data, but are limited in handling dynamic and complex features because they require prior knowledge of the number of clusters.
no code implementations • 19 May 2023 • Xinyi Li, Hu Cao, Yinlong Liu, Xueli Liu, Feihu Zhang, Alois Knoll
Moreover, our method can be adapted to address the challenging problem of simultaneous pose and registration.
no code implementations • 19 May 2023 • Rui Song, Lingjuan Lyu, Wei Jiang, Andreas Festag, Alois Knoll
Machine learning (ML) has revolutionized transportation systems, enabling autonomous driving and smart traffic services.
no code implementations • 29 Apr 2023 • Mingyang Wang, Zhenshan Bing, Xiangtong Yao, Shuai Wang, Hang Su, Chenguang Yang, Kai Huang, Alois Knoll
On MuJoCo and Meta-World benchmarks, MoSS outperforms prior works in terms of asymptotic performance, sample efficiency (3-50x faster), adaptation efficiency, and generalization robustness on broad and diverse task distributions.
no code implementations • 24 Apr 2023 • Soubarna Banik, Patricia Gschoßmann, Alejandro Mendoza Garcia, Alois Knoll
We show that our proposed method compares favorably with the state-of-the-art (SoA).
1 code implementation • ICML 2023 • Yuning Cui, Wenqi Ren, Sining Yang, Xiaochun Cao, Alois Knoll
We present IRNeXt, a simple yet effective convolutional network architecture for image restoration.
Ranked #4 on Image Dehazing on SOTS Outdoor
1 code implementation • Conference 2023 • Yuning Cui, Yi Tao, Zhenshan Bing, Wenqi Ren, Xinwei Gao, Xiaochun Cao, Kai Huang, Alois Knoll
Image restoration aims to reconstruct the latent sharp image from its corrupted counterpart.
Ranked #1 on Deblurring on RSBlur
1 code implementation • CVPR 2023 • Fengyi Shen, Akhil Gurram, Ziyuan Liu, He Wang, Alois Knoll
Domain adaptive semantic segmentation methods commonly utilize stage-wise training, consisting of a warm-up and a self-training stage.
1 code implementation • 4 Apr 2023 • Rui Song, Runsheng Xu, Andreas Festag, Jiaqi Ma, Alois Knoll
Our findings suggest that FedBEVT outperforms the baseline approaches in all four use cases, demonstrating the potential of our approach for improving BEV perception in autonomous driving.
no code implementations • ICCV 2023 • Tianhang Wang, Guang Chen, Kai Chen, Zhengfa Liu, Bo Zhang, Alois Knoll, Changjun Jiang
To verify our algorithm, we conducted experiments on the V2X-Sim and OPV2V datasets.
1 code implementation • ICCV 2023 • Haotian Liu, Guang Chen, Sanqing Qu, Yanping Zhang, Zhijun Li, Alois Knoll, Changjun Jiang
In this paper, we argue that temporal continuity is a vital element of event-based optical flow and propose a novel Temporal Motion Aggregation (TMA) approach to unlock its potential.
no code implementations • 15 Mar 2023 • Liguo Zhou, Tianhao Lin, Alois Knoll
To address the above challenges, based on extensive literature research, this paper analyzes methods for improving and optimizing mainstream object detection algorithms from the perspective of evolution of one-stage and two-stage object detection algorithms.
no code implementations • 12 Mar 2023 • Haichuan Li, Liguo Zhou, Zhenshan Bing, Marzana Khatun, Rolf Jung, Alois Knoll
Several autonomous driving strategies have been applied to autonomous vehicles, especially in the collision avoidance area.
no code implementations • 12 Mar 2023 • Haichuan Li, Liguo Zhou, Alois Knoll
In this paper, we propose a CNN-based method that overcomes the limitation by establishing feature correlations between regions in sequential images using variants of attention.
no code implementations • 25 Feb 2023 • Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen, Jan Peters, Alois Knoll
Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment.
no code implementations • 23 Feb 2023 • Hanzhen Zhang, Liguo Zhou, Ruining Wang, Alois Knoll
Using real road testing to optimize autonomous driving algorithms is time-consuming and capital-intensive.
1 code implementation • ICCV 2023 • Yuning Cui, Wenqi Ren, Xiaochun Cao, Alois Knoll
Image restoration aims to reconstruct a sharp image from its degraded counterpart, which plays an important role in many fields.
Ranked #7 on Image Dehazing on SOTS Outdoor
no code implementations • 31 Dec 2022 • Wei Cao, Liguo Zhou, Yuhong Huang, Alois Knoll
There are many artificial intelligence algorithms for autonomous driving, but directly installing these algorithms on vehicles is unrealistic and expensive.
no code implementations • 11 Dec 2022 • Rui Song, Liguo Zhou, Lingjuan Lyu, Andreas Festag, Alois Knoll
To address this bottleneck, we introduce a residual-based federated learning framework (ResFed), where residuals rather than model parameters are transmitted in communication networks for training.
1 code implementation • 21 Nov 2022 • Fengyi Shen, Zador Pataki, Akhil Gurram, Ziyuan Liu, He Wang, Alois Knoll
In this paper, we propose LoopDA for domain adaptive nighttime semantic segmentation.
no code implementations • 21 Sep 2022 • Xiangtong Yao, Zhenshan Bing, Genghang Zhuang, KeJia Chen, Hongkuan Zhou, Kai Huang, Alois Knoll
We propose a dual-MDP meta-reinforcement learning method that enables learning new tasks efficiently with symmetrical behaviors and language instructions.
no code implementations • 21 Sep 2022 • Brian Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen, Alois Knoll
We consider the safety-oriented performance of 3D object detectors in autonomous driving contexts.
1 code implementation • 7 Sep 2022 • Syed Qutub, Florian Geissler, Yang Peng, Ralf Grafe, Michael Paulitsch, Gereon Hinz, Alois Knoll
The evaluation of several representative object detection models shows that even a single bit flip can lead to a severe silent data corruption event with potentially critical safety implications, with e. g., up to (much greater than) 100 FPs generated, or up to approx.
2 code implementations • 24 Aug 2022 • Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag, Carsten Trinitis, Martin Schulz, Alois Knoll
In federated learning, all networked clients contribute to the model training cooperatively.
no code implementations • 28 Jun 2022 • Haitao Meng, Changcai Li, Gang Chen, Alois Knoll
In the experiments, we develop a system with a less powerful stereo matching predictor and adopt the proposed refinement schemes to improve the accuracy.
no code implementations • 17 Jun 2022 • Rui Song, Anupama Hegde, Numan Senel, Alois Knoll, Andreas Festag
Specifically, when the measurement error from the sensors (also referred as measurement noise) is unknown and time varying, the performance of the data fusion process is restricted, which represents a major challenge in the calibration of sensors.
no code implementations • 13 Jun 2022 • Josip Josifovski, Mohammadhossein Malmir, Noah Klarmann, Bare Luka Žagar, Nicolás Navarro-Guerrero, Alois Knoll
Fully randomized simulations and fine-tuning show differentiated results and translate better to the real robot than the other approaches tested.
1 code implementation • 20 May 2022 • Shangding Gu, Long Yang, Yali Du, Guang Chen, Florian Walter, Jun Wang, Yaodong Yang, Alois Knoll
To establish a good foundation for future research in this thread, in this paper, we provide a review for safe RL from the perspectives of methods, theory and applications.
1 code implementation • 2 May 2022 • Ekim Yurtsever, Emeç Erçelik, MingYu Liu, Zhijie Yang, Hanzhen Zhang, Pınar Topçam, Maximilian Listl, Yılmaz Kaan Çaylı, Alois Knoll
Our main contribution leverages learned flow and motion representations and combines a self-supervised backbone with a supervised 3D detection head.
no code implementations • 13 Apr 2022 • Christian Creß, Walter Zimmer, Leah Strand, Venkatnarayanan Lakshminarasimhan, Maximilian Fortkord, Siyi Dai, Alois Knoll
As part of the first set of data, which we describe in this paper, we provide camera and LiDAR frames from two overhead gantry bridges on the A9 autobahn with the corresponding objects labeled with 3D bounding boxes.
1 code implementation • 1 Apr 2022 • Rui Song, Liguo Zhou, Venkatnarayanan Lakshminarasimhan, Andreas Festag, Alois Knoll
Considering the individual heterogeneity of data distribution, computational and communication capabilities across traffic agents and roadside units, we employ a novel method that addresses the heterogeneity of different aggregation layers of the framework architecture, i. e., aggregation in layers of roadside units and cloud.
no code implementations • 31 Mar 2022 • Walter Zimmer, Emec Ercelik, Xingcheng Zhou, Xavier Jair Diaz Ortiz, Alois Knoll
The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection methods, datasets, and challenges.
no code implementations • 31 Mar 2022 • Walter Zimmer, Marcus Grabler, Alois Knoll
This work aims to address the challenges in domain adaptation of 3D object detection using infrastructure LiDARs.
no code implementations • 11 Mar 2022 • Marco Oliva, Soubarna Banik, Josip Josifovski, Alois Knoll
We derive a graph representation that models the physical structure of the manipulator and combines the robot's internal state with a low-dimensional description of the visual scene generated by an image encoding network.
1 code implementation • 25 Feb 2022 • Javier López-Randulfe, Nico Reeb, Negin Karimi, Chen Liu, Hector A. Gonzalez, Robin Dietrich, Bernhard Vogginger, Christian Mayr, Alois Knoll
After several decades of continuously optimizing computing systems, the Moore's law is reaching itsend.
no code implementations • 8 Feb 2022 • Brian Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen, Alois Knoll
As an emerging type of Neural Networks (NNs), Transformers are used in many domains ranging from Natural Language Processing to Autonomous Driving.
no code implementations • 14 Jan 2022 • Benedikt Feldotto, Cristian Soare, Alois Knoll, Piyanee Sriya, Sarah Astill, Marc de Kamps, Samit Chakrabarty
We use our framework to analyze raw EMG data collected during an isometric knee extension study to identify synergies that drive a musculoskeletal lower limb model.
1 code implementation • 30 Nov 2021 • Fengyi Shen, Akhil Gurram, Ahmet Faruk Tuna, Onay Urfalioglu, Alois Knoll
Due to the difficulty of obtaining ground-truth labels, learning from virtual-world datasets is of great interest for real-world applications like semantic segmentation.
no code implementations • 27 Oct 2021 • Stefan Böhm, Martin Neumayer, Oliver Kramer, Alexander Schiendorfer, Alois Knoll
Cutting and Packing problems are occurring in different industries with a direct impact on the revenue of businesses.
3 code implementations • 6 Oct 2021 • Shangding Gu, Jakub Grudzien Kuba, Munning Wen, Ruiqing Chen, Ziyan Wang, Zheng Tian, Jun Wang, Alois Knoll, Yaodong Yang
To fill these gaps, in this work, we formulate the safe MARL problem as a constrained Markov game and solve it with policy optimisation methods.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 22 Sep 2021 • Zhenshan Bing, Amir EI Sewisy, Genghang Zhuang, Florian Walter, Fabrice O. Morin, Kai Huang, Alois Knoll
As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment.
no code implementations • 23 Aug 2021 • Soubarna Banik, Alejandro Mendoza Garcia, Lorenz Kiwull, Steffen Berweck, Alois Knoll
We evaluate it on our rehab datasets, and observe that the performance degrades significantly from non-rehab to rehab, highlighting the need for these datasets.
1 code implementation • 8 Aug 2021 • Zhenshan Bing, Lukas Knak, Fabrice Oliver Robin, Kai Huang, Alois Knoll
Recent state-of-the-art artificial agents lack the ability to adapt rapidly to new tasks, as they are trained exclusively for specific objectives and require massive amounts of interaction to learn new skills.
no code implementations • 21 May 2021 • Chih-Hong Cheng, Alois Knoll, Hsuan-Cheng Liao
Within the context of autonomous driving, safety-related metrics for deep neural networks have been widely studied for image classification and object detection.
1 code implementation • 21 May 2021 • Soubarna Banik, Alejandro Mendoza Gracia, Alois Knoll
We propose one such graph convolutional network named PoseGraphNet for 3D human pose regression from 2D poses.
Ranked #201 on 3D Human Pose Estimation on Human3.6M
1 code implementation • 25 Apr 2021 • Emeç Erçelik, Ekim Yurtsever, Alois Knoll
Furthermore, ablation studies reinforce that the subject of improvement is temporal fusion and show the effects of different placements of TFM in the object detection pipeline.
no code implementations • 12 Apr 2021 • Corvin Deboeser, Jordan Ivanchev, Thomas Braud, Alois Knoll, David Eckhoff, Alberto Sangiovanni-Vincentelli
This paper introduces the SEAD framework that simplifies the process of designing and describing autonomous vehicle platooning manoeuvres.
2 code implementations • 7 Apr 2021 • Sanqing Qu, Guang Chen, Zhijun Li, Lijun Zhang, Fan Lu, Alois Knoll
Traditional methods mainly focus on foreground and background frames separation with only a single attention branch and class activation sequence.
Ranked #5 on Weakly Supervised Action Localization on THUMOS14
Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1
no code implementations • 10 Mar 2021 • Damir Bojadžić, Julian Kunze, Dinko Osmanković, Mohammadhossein Malmir, Alois Knoll
Therefore, the algorithm presented in this paper needs to anticipate and avoid dynamic obstacles, such as pedestrians or bicycles, but also be fast enough in order to work in real-time so that it can adapt to changes in the environment.
Motion Planning Trajectory Planning Robotics
1 code implementation • 5 Mar 2021 • Christoph Schöller, Alois Knoll
In our work, we model motion prediction directly as a density estimation problem with a normalizing flow between a noise distribution and the future motion distribution.
1 code implementation • 10 Feb 2021 • Kai Chen, Guang Chen, Dan Xu, Lijun Zhang, Yuyao Huang, Alois Knoll
Although Transformer has made breakthrough success in widespread domains especially in Natural Language Processing (NLP), applying it to time series forecasting is still a great challenge.
no code implementations • 5 Feb 2021 • Julian Bernhard, Robert Gieselmann, Klemens Esterle, Alois Knoll
With Deep Reinforcement Learning, optimal driving strategies for such problems can be derived also for higher-dimensional problems.
no code implementations • 5 Feb 2021 • Julian Bernhard, Alois Knoll
In this work, we adopt this safety objective for interactive planning.
no code implementations • 5 Feb 2021 • Julian Bernhard, Stefan Pollok, Alois Knoll
Specifically, we first learn an optimal policy in an uncertain environment with Deep Distributional Reinforcement Learning.
Distributional Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 25 Jan 2021 • Hu Cao, Guang Chen, Zhijun Li, Jianjie Lin, Alois Knoll
Extensive experiments on two public grasping datasets, Cornell and Jacquard demonstrate the state-of-the-art performance of our method in balancing accuracy and inference speed.
Ranked #1 on Robotic Grasping on Jacquard dataset
no code implementations • 18 Jan 2021 • Emmanouil Angelidis, Emanuel Buchholz, Jonathan Patrick Arreguit O'Neil, Alexis Rougè, Terrence Stewart, Axel von Arnim, Alois Knoll, Auke Ijspeert
In this work we propose a spiking CPG neural network and its implementation on neuromorphic hardware as a means to control a simulated lamprey model.
1 code implementation • 18 Dec 2020 • Fan Lu, Guang Chen, Sanqing Qu, Zhijun Li, Yinlong Liu, Alois Knoll
Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras.
no code implementations • 16 Nov 2020 • Sanqing Qu, Guang Chen, Dan Xu, Jinhu Dong, Fan Lu, Alois Knoll
At each time step, this sampling strategy first estimates current action progression and then decide what temporal ranges should be used to aggregate the optimal supplementary features.
1 code implementation • NeurIPS 2020 • Fan Lu, Guang Chen, Yinlong Liu, Zhongnan Qu, Alois Knoll
To tackle the information loss of random sampling, we exploit a novel random dilation cluster strategy to enlarge the receptive field of each sampled point and an attention mechanism to aggregate the positions and features of neighbor points.
no code implementations • 28 Sep 2020 • Benedikt Feldotto, Heiko Lengenfelder, Alois Knoll
We analyze the individual neuron activity distribution in the network, introduce a pruning algorithm to reduce network size keeping the performance, and with these dense network representations we spot correlations of neuron activity patterns among networks trained for robot manipulators with different joint number.
1 code implementation • 27 Jul 2020 • Zhenshan Bing, Matthias Brucker, Fabrice O. Morin, Kai Huang, Alois Knoll
In this paper, we propose graph-based hindsight goal generation (G-HGG), an extension of HGG selecting hindsight goals based on shortest distances in an obstacle-avoiding graph, which is a discrete representation of the environment.
2 code implementations • 1 Jul 2020 • Klemens Esterle, Luis Gressenbuch, Alois Knoll
We contribute a formalized set of traffic rules for single-direction carriageways, such as on highways.
Robotics
no code implementations • 27 Jun 2020 • Maximilian Kraus, Seyed Majid Azimi, Emec Ercelik, Reza Bahmanyar, Peter Reinartz, Alois Knoll
Due to the challenges such as the large number and the tiny size of the pedestrians (e. g., 4 x 4 pixels) with their similar appearances as well as different scales and atmospheric conditions of the images with their extremely low frame rates (e. g., 2 fps), current state-of-the-art algorithms including the deep learning-based ones are unable to perform well.
2 code implementations • 22 Jun 2020 • Patrick Hart, Alois Knoll
We show that graph neural networks are capable of handling scenarios with a varying number and order of vehicles during training and application.
2 code implementations • 20 Mar 2020 • Patrick Hart, Alois Knoll
If a policy can handle all counterfactual worlds well, it either has seen similar situations during training or it generalizes well and is deemed to be fit enough to be executed in the actual world.
no code implementations • 17 Mar 2020 • Elie Aljalbout, Florian Walter, Florian Röhrbein, Alois Knoll
This model is the main focus of this work, as its contribution is not limited to engineering but also applicable to neuroscience.
no code implementations • 10 Mar 2020 • Zhenshan Bing, Claus Meschede, Guang Chen, Alois Knoll, Kai Huang
Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a promising potential for accomplishing fast and energy-efficient computing, which is beneficial to mobile robotic applications.
no code implementations • 2 Mar 2020 • Michael Hammann, Maximilian Kraus, Sina Shafaei, Alois Knoll
Identity recognition in a car cabin is a critical task nowadays and offers a great field of applications ranging from personalizing intelligent cars to suit drivers physical and behavioral needs to increasing safety and security.
no code implementations • 16 Jun 2019 • Annkathrin Krämmer, Christoph Schöller, Dhiraj Gulati, Venkatnarayanan Lakshminarasimhan, Franz Kurz, Dominik Rosenbaum, Claus Lenz, Alois Knoll
An Intelligent Infrastructure System can fill in the gaps in a vehicle's perception and extend its field of view by providing additional detailed information about its surroundings, in the form of a digital model of the current traffic situation, i. e. a digital twin.
1 code implementation • 14 Jun 2019 • Thomas Brunner, Frederik Diehl, Alois Knoll
Many optimization methods for generating black-box adversarial examples have been proposed, but the aspect of initializing said optimizers has not been considered in much detail.
no code implementations • 19 May 2019 • Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll
Semantic Embeddings are a popular way to represent knowledge in the field of zero-shot learning.
1 code implementation • 29 Apr 2019 • Yinlong Liu, Alois Knoll, Guang Chen
Accordingly, we propose a vertical direction estimation method by considering the relationship between the vertical frame and horizontal frames.
1 code implementation • 18 Apr 2019 • Christoph Schöller, Maximilian Schnettler, Annkathrin Krämmer, Gereon Hinz, Maida Bakovic, Müge Güzet, Alois Knoll
Most intelligent transportation systems use a combination of radar sensors and cameras for robust vehicle perception.
no code implementations • 25 Mar 2019 • Yinlong Liu, Xuechen Li, Manning Wang, Guang Chen, Zhijian Song, Alois Knoll
In this paper, we consider pairwise constraints and propose a globally optimal algorithm for solving the absolute pose estimation problem.
2 code implementations • 19 Mar 2019 • Christoph Schöller, Vincent Aravantinos, Florian Lay, Alois Knoll
Our work shows how neural networks for pedestrian motion prediction can be thoroughly evaluated and our results indicate which research directions for neural motion prediction are promising in future.
no code implementations • 4 Mar 2019 • Frederik Diehl, Thomas Brunner, Michael Truong Le, Alois Knoll
We show that prediction error in scenarios with much interaction decreases by 30% compared to a model that does not take interactions into account.
3 code implementations • ICCV 2019 • Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll
We consider adversarial examples for image classification in the black-box decision-based setting.
no code implementations • 17 Aug 2018 • Mingchuan Zhou, Mahdi Hamad, Jakob Weiss, Abouzar Eslami, Kai Huang, Mathias Maier, Chris P. Lohmann, Nassir Navab, Alois Knoll, M. Ali Nasseri
Ophthalmic microsurgery is known to be a challenging operation, which requires very precise and dexterous manipulation.
no code implementations • 6 Dec 2017 • Guang Chen, Shu Liu, Kejia Ren, Zhongnan Qu, Changhong Fu, Gereon Hinz, Alois Knoll
However, the mobile sensing perception brings new challenges for how to efficiently analyze and intelligently interpret the deluge of IoT data in mission- critical services.
no code implementations • ICCV 2015 • Philipp Heise, Brian Jensen, Sebastian Klose, Alois Knoll
We formulate the combined multi-view stereo reconstruction and refinement as a variational optimization problem.