4 accepted papers
Discrete Wavelet Transform (DWT) has been widely explored to enhance the performance of image super-resolution (SR). Despite some DWT-based methods improving SR by capturing fine-grained frequency signals, most existing approaches neglect the interrelations among multi-scale frequency sub-bands, res…
The ill-posed nature of monocular 3D geometry (depth map and surface normals) estimation makes it rely mostly on data-driven approaches such as Deep Neural Networks (DNN). However, data acquisition of surface normals, especially the reliable normals, is acknowledged difficult. Commonly, reconstructi…
With the continual expansion of face datasets, feature-based distillation prevails for large-scale face recognition. In this work, we attempt to remove identity supervision in student training, to spare the GPU memory from saving massive class centers. However, this naive removal leads to inferior d…
"Deep Metric Learning (DML) serves to learn an embedding function to project semantically similar data into nearby embedding space and plays a vital role in many applications, such as image retrieval and face recognition. However, the performance of DML methods often highly depends on sampling metho…