This study proposes and evaluates a learning-based patch-wise segmentation network and a newly proposed Consistency Check as post-processing step. The combination of the learned segmentation and Consistency Check reaches a high segmentation performance with an average IoU score of 0.924 on the test ...
【depth-consistency】 放弃相邻图像间不一致的深度 方法还是按p的预测深度d(p)把它投影到另一张图的p’上,再按照d(p’)投会来,如果误差小则认为满足一致性,至少要做到ref跟两张src的一致性才通过测试 创新点在于:对于有相机参数真值的点采用双线性插值方法,否则采用depth-consistency first策略,Fig 5略 Experim...
【depth-consistency】 放弃相邻图像间不一致的深度 方法还是按p的预测深度d§把它投影到另一张图的p’上,再按照d(p’)投会来,如果误差小则认为满足一致性,至少要做到ref跟两张src的一致性才通过测试 创新点在于:对于有相机参数真值的点采用双线性插值方法,否则采用depth-consistency first策略,Fig 5略 Experiment...
In an attempt to fill this gap, we propose a unified pixel- and patch-wise self-supervised learning framework, called PiPa, for domain adaptive semantic segmentation that facilitates intra-image pixel-wise correlations and patch-wise semantic consistency against different contexts. The proposed ...