Camera-only Bird’s-Eye-View (BEV) networks are gaining significant traction in the field of autonomous driving perception. They can transform six images providing a 360-degree view surrounding a vehicle into a comprehensive, topdown view similar to a bird’s perspective. This work focuses on the camera-only BEV semantic segmentation task, enabling the network to segment various elements, primarily vehicles, within this view. Sophia Sirko-Galouchenko is a first-year PhD student at Sorbonne University in Paris and Valeo.ai. Her paper on bird’s-eyeview perception in autonomous driving was presented by colleagues on Monday during a poster session at the Workshop on Autonomous Driving. She speaks to us about the work. 18 DAILY CVPR Friday Workshop Poster UKRAINE CORNER Russian Invasion of Ukraine CVPR condemns in the strongest possible terms the actions of the Russian Federation government in invading the sovereign state of Ukraine and engaging in war against the Ukrainian people. We express our solidarity and support for the people of Ukraine and for all those who have been adversely affected by this war. OccFeat: Self-supervised Occupancy Feature Prediction for Pre-training BEV Segmentation Networks
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