Memory Based Video Scene Parsing
This work addresses video scene parsing for computer vision applications, but it is incremental as it focuses on a specific challenge submission.
The authors tackled video scene parsing by developing a solution for the Video Scene Parsing in the Wild Challenge, achieving a mIoU of 57.44 and securing second place.
Video scene parsing is a long-standing challenging task in computer vision, aiming to assign pre-defined semantic labels to pixels of all frames in a given video. Compared with image semantic segmentation, this task pays more attention on studying how to adopt the temporal information to obtain higher predictive accuracy. In this report, we introduce our solution for the 1st Video Scene Parsing in the Wild Challenge, which achieves a mIoU of 57.44 and obtained the 2nd place (our team name is CharlesBLWX).