… At last, we introduce the variant model to resolve the extended problem of joint frame
super-… Compare to the model (PRF4or BIN4) in our previous paper [11], we adopt a deeper …

… At the l-th image pyramid level, we firstly initialize the bi-directional flow by ×2 upsampling
Fl… Deep generative image models using a laplacian pyramid of adversarial networks. NeurIPS, …

… Other challenges include (i) dependency of haze transmission on unknown depth that varies
at … Combining a haze imaging model and a soft matting interpolation method, the authors …

… Deep Feature Interpolation (DFI), a new datadriven baseline for automatic high-resolution
image … In our setting, we are provided with a test image x which we would like to change in a …

… a set of multi-scale depth image features. However, the feature … In image object detection,
scale variability of objects and … Nearest neighbor interpolation and bilinear interpolation em…

… Enhanced Deep Pyramid Network (EDPN) for blurry image restoration … in the degraded
image. Specifically, we design two … to solve image super-resolution (SR), including interpolation-…

… total generalized variation method to improve the quality of HR depth maps. Based on this, …
-images. We downsampled the HR sub-images by bicubic interpolation to obtain LR depth …

… learning approach of the ResNet [6] with deep recursion. We note that the above methods use
bicubic interpolation to pre-upsample input LR images … We compare three variations of the …

… with trilinear interpolation to obtain \(F_i \in \{F_1, F_2,F_3\}\) (… }\), which is a variant of LapIRN
parameterizing the deformation … deep Laplacian pyramid networks for deformable image …

… Pyramid Dilated Network (PyDiNet), a new deep neural network architecture to solve the
challenging variations in the size of objects in medical images. … by a bilinear interpolation to up-…