Despite recent advances in autonomous driving systems, accidents such as the fatal Uber
crash in 2018 show these systems are still susceptible to edge cases. Such systems must be …

Motion prediction is essential for safe and efficient autonomous driving. However, the
inexplicability and uncertainty of complex artificial intelligence models may lead to …

Autonomous robots deal with unexpected scenarios in real environments. Given input
images, various visual perception tasks can be performed, eg, semantic segmentation …

Integrating an efficient and robust iris segmentation-quality estimation module in iris
biometric systems will undoubtedly enhance its performance and competitive advantage. It …

We propose the concept of error-reversing autoencoders (ERA) for correcting pixel-wise
errors made by an arbitrary semantic segmentation model. For this, we reframe the …

In the emerging field of video coding for machines, video datasets with pristine video quality
and high-quality annotations are required for a comprehensive evaluation. However …

Efficient and accurate segmentation of unseen objects is crucial for robotic manipulation.
However, it remains challenging due to over-or under-segmentation. Although existing …

The quality of semantic image segmentation models can be affected by external factors such
as weather or daytime. Those factors can lead to safety-critical mistakes. In this work, we …

Multimodal object detection fuses different sensors such as camera or LIDAR to improve the
detection performance. However, individual sensor inputs can also be detrimental to a …

Autonomous robots deal with unexpected scenarios in real environments. Given input
images, various visual perception tasks can be performed, eg, semantic segmentation …