Understanding Road Layout From Videos as a Whole
CVPR 2020 | We address the problem of inferring the layout of complex road scenes from video sequences. To this end, we formulate it as a top-view road attributes prediction problem, and our goal is to predict these attributes for each frame both accurately and consistently. In contrast to prior work, we exploit the following three novel aspects: (i) leveraging camera motions in videos (ii) including context cues and (iii) incorporating long-term video information. Specifically, we introduce a model that aims to enforce prediction consistency in videos.