Unsupervised Learning of Visual Representations by Solving Shuffled Long Video-Frames Temporal Order Prediction

We propose a hierarchical approach for making long-term predictions of future frames. To avoid inherent compounding errors in recursive pixel-level prediction, we propose to first estimate high-level structure in the input frames, then predict how that ...

This study proposes a system to estimate the depth order of regions belonging to a monocular image sequence. For each frame, the regions are ordered according to their relative depth using information from the previous and following frames. The algorithm ...

Deep learning based depth estimation methods have been proven effective and promising, especially learning depth from monocular video. Depth-from-video is the real sense of unsupervised depth estimation, as it doesn’t need depth ground truth or ...