We observe that these proposed schemes are capable of facilitating the learning of discriminative feature representations.
To obtain a single model that works across multiple target domains, we propose to simultaneously learn a student model which is trained to not only imitate the output of each expert on the corresponding target domain, but also to pull different expert close to each other with regularization on their weights.
Video super-resolution plays an important role in surveillance video analysis and ultra-high-definition video display, which has drawn much attention in both the research and industrial communities.
Ranked #1 on Video Super-Resolution on UDM10 - 4x upscaling
Most video super-resolution methods super-resolve a single reference frame with the help of neighboring frames in a temporal sliding window.
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention.
Video-based person re-identification has drawn massive attention in recent years due to its extensive applications in video surveillance.