Toyota Motor Europe

Katholieke Universiteit Leuven

Toyota Jidosha Kabushiki Kaisha

Eth Zurich

Katholieke Universiteit Leuven, Ku Leuven R&d

Hiroaki Shimizu

Luc Van Gool

Marc Proesmans

Davy Neven

Frank Verbiest

Kazuki Tamura

Dengxin Dai

Bert De Brabandere

Christos Sakaridis

Jonas Heylen

Bruno Dawagne

Bert Debrabandere

A system for producing a virtual image view for a vehicle is provided. The system includes one or more image capture means configured to capture image data in proximity to the vehicle, the image data being defined at least in part by first viewpoint parameters, and to provide an identifier identifying the respective one or more image capture means, storage means configured to store a plurality of virtualization records containing conversion information related to a virtualized viewpoint and a plurality of image capture means, and processing means. The processing means are configured to receive the captured image data, convert the first viewpoint parameters of the captured image data into virtual viewpoint parameters based on the conversion information associated with a virtualization record stored by the storage means, to result in the virtual image view, wherein the virtualization record is identified at least based on the identifier, and execute at least one driver assistance and/or automated driving function based on the virtual image view.

Systems and method for image normalization

A system and a method for training a model to be used for semantic segmentation of images, comprising:

Method and a system training a model to perform semantic segmentation on foggy images

A system and a method for processing a plurality of images, each image of the plurality of images being acquired by a respective image acquisition module of a vehicle and each image acquisition module being oriented outwardly with respect to the vehicle, the method comprising:

Method and system for processing a plurality of images so as to detect lanes on a road

A system and a method for processing an image so as to perform instance segmentation. The system/method includes: a—inputting (S) the image (IMG) to a first neural network configured to output an affinity graph (AF), and b—inputting (S), to a second neural network, the affinity graph and a predefined seed-map (SM), so as to determine whether other pixels belong to a same instance, and set at a first value the value of the other pixels determined as belonging to the same instance.

Method and system for processing an image and performing instance segmentation using affinity graphs

Growing community of inventors

Brussels, Belgium

Hiroaki Shimizu