4 accepted papers
Recently unsupervised learning of depth from videos has made remarkable progress and the results are comparable to fully supervised methods in outdoor scenes like KITTI. However, there still exist great challenges when directly applying this technology in indoor environments, e.g., large areas of no…
Unsupervised depth learning takes the appearance difference between a target view and a view synthesized from its adjacent frame as supervisory signal. Since the supervisory signal only comes from images themselves, the resolution of training data significantly impacts the performance. High-resoluti…
In non-destructive testing of three-dimensional media, the total focusing method (TFM) draws attentions of numerous researchers owing to its ability to provide image with superior quality. But its application in multilayered media is limited by the computation complexity of calculating point of inci…
In imaging of multilayered object, total focusing method (TFM) combined with ray-tracing appeals to numerous researchers because of its superior image quality. But lots of iterative computation to calculate the incident points greatly increases its processing time. Based on line scan-conversion algo…