5 papers
Searching for Controllable Image Restoration Networks
Heewon Kim, Sungyong Baik, Myungsub Choi +2
Diverse user preferences over images have recently led to a great amount of interest in controlling the imagery effects for image restoration tasks. However, existing methods requi…
Meta-Learning with Adaptive Hyperparameters
Sungyong Baik, Myungsub Choi, Janghoon Choi +2
Despite its popularity, several recent works question the effectiveness of MAML when test tasks are different from training tasks, thus suggesting various task-conditioned methodol…
AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Seungjun Nah, Sanghyun Son, Radu Timofte +1
Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challeng…
Fine-Grained Neural Architecture Search
Heewon Kim, Seokil Hong, Bohyung Han +2
We present an elegant framework of fine-grained neural architecture search (FGNAS), which allows to employ multiple heterogeneous operations within a single layer and can even gene…
Enhanced Deep Residual Networks for Single Image Super-Resolution
Bee Lim, Sanghyun Son, Heewon Kim +2
Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved p…