FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

Face Super-Resolution (SR) is a domain-specific super-resolution problem. The specific facial prior knowledge could be leveraged for better super-resolving face images. We present a novel deep end-to-end trainable Face Super-Resolution Network (FSRNet), which makes full use of the geometry prior, i.e., facial landmark heatmaps and parsing maps, to super-resolve very low-resolution (LR) face images without well-aligned requirement. Specifically, we first construct a coarse SR network to recover a coarse high-resolution (HR) image. Then, the coarse HR image is sent to two branches: a fine SR encoder and a prior information estimation network, which extracts the image features, and estimates landmark heatmaps/parsing maps respectively. Both image features and prior information are sent to a fine SR decoder to recover the HR image. To further generate realistic faces, we propose the Face Super-Resolution Generative Adversarial Network (FSRGAN) to incorporate the adversarial loss into FSRNet. Moreover, we introduce two related tasks, face alignment and parsing, as the new evaluation metrics for face SR, which address the inconsistency of classic metrics w.r.t. visual perception. Extensive benchmark experiments show that FSRNet and FSRGAN significantly outperforms state of the arts for very LR face SR, both quantitatively and qualitatively. Code will be made available upon publication.Comment: Chen and Tai contributed equally to this pape

Finite Element Investigation on Load Carrying Capacity of Corroded RC Beam Based on Bond-Slip

The finite element (FE) investigation on the load carrying capacity of corroded RC beam is carried out based on the bond-slip between the steel bars and concrete. In the numerical simulation, several FE models of RC simply supported beam with different corrosion ratios were built using ANSYS. In these FE models, element of Solid65 was used to simulate concrete, element of Link8 was used for bars and element of Combin39 was adopted to simulate the bond and bond-slip between bars and concrete. The effect of corrosion ratio on bonding force between bars and concrete was simulated by adjusting the parameter of Combin39. Besides, the reduction of bars section area and decrease of bars yielding stress were also considered for calculating the load carrying capacity of corroded RC beam with different corrosion ratios. The results show that as the corrosion ratio increases the stiffness of corroded beam would decrease, slip between bars and concrete would be larger and ductile failure of RC beam would turn to brittle failure. The load carrying capacity of corroded RC beam would obviously deteriorate and descending speed is the fastest when the corrosion rate falls in the range of 4%-7%