An efficient and accurate multi-level cascaded recurrent network for stereo matching
Abstract With the advent of Transformer-based convolutional neural networks, stereo matching algorithms have achieved state-of-the-art accuracy in disparity estimation.Nevertheless, this method requires much model inference time, which is the main reason limiting its application in many vision tasks and robots.Facing the trade-off problem between a