Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

Gérin, Benoît; Halin, Anaïs; Cioppa, Anthony; Henry, Maxim; Ghanem, Bernard; Macq, Benoît; De Vleeschouwer, Christophe; Van Droogenbroeck, Marc

doi:10.1109/cvprw63382.2024.00450

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2024

DOI: 10.1109/cvprw63382.2024.00450

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Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

Benoît Gérin,

Anaïs Halin,

Anthony Cioppa

et al.

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Cited by 1 publication

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Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison

Kozłowski,

Racewicz,

Wierzbicki

2024

Applied Sciences

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The integration of advanced image analysis using artificial intelligence (AI) is pivotal for the evolution of autonomous vehicles (AVs). This article provides a thorough review of the most significant datasets and latest state-of-the-art AI solutions employed in image analysis for AVs. Datasets such as Cityscapes, NuScenes, CARLA, and Talk2Car form the benchmarks for training and evaluating different AI models, with unique characteristics catering to various aspects of autonomous driving. Key AI methodologies, including Convolutional Neural Networks (CNNs), Transformer models, Generative Adversarial Networks (GANs), and Vision Language Models (VLMs), are discussed. The article also presents a comparative analysis of various AI techniques in real-world scenarios, focusing on semantic image segmentation, 3D object detection, vehicle control in virtual environments, and vehicle interaction using natural language. Simultaneously, the roles of multisensor datasets and simulation platforms like AirSim, TORCS, and SUMMIT in enriching the training data and testing environments for AVs are highlighted. By synthesizing information on datasets, AI solutions, and comparative performance evaluations, this article serves as a crucial resource for researchers, developers, and industry stakeholders, offering a clear view of the current landscape and future directions in autonomous vehicle image analysis technologies.

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Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison

Kozłowski,

Racewicz,

Wierzbicki

2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

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Multi-Stream Cellular Test-Time Adaptation of Real-Time Models Evolving in Dynamic Environments

Cited by 1 publication

References 39 publications

Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison

Image Analysis in Autonomous Vehicles: A Review of the Latest AI Solutions and Their Comparison

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