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...
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 ...
This difference can be beneficial for deepfake detection, as it lets the model scrutinize the overall structure and consistency of an image. Robustness to Manipulations: ViT models might exhibit increased robustness to common manipulation techniques used in deepfake generation. Their attention mechanisms ...