Search Results for author:
Found 8 papers, 4 papers with code
List-Mode PET Image Reconstruction Using Deep Image Prior
However, the application of deep learning techniques to list-mode PET image reconstruction has not been progressed because list data is a sequence of bit codes and unsuitable for processing by convolutional neural networks (CNN).
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling
Instead of directly feeding consecutive frames into a VSR model, we propose to compute the temporal difference between frames and divide those pixels into two subsets according to the level of difference.
Towards Discriminative Representation Learning for Unsupervised Person Re-identification
We observe that these proposed schemes are capable of facilitating the learning of discriminative feature representations.
Multi-Target Domain Adaptation with Collaborative Consistency Learning
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.
Ranked #3 on
Domain Adaptation
on GTAV to Cityscapes+Mapillary
Revisiting Temporal Modeling for Video Super-resolution
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 SPMCS - 4x upscaling
Video Super-Resolution with Recurrent Structure-Detail Network
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 with Temporal Group Attention
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention.
Intra-clip Aggregation for Video Person Re-identification
Video-based person re-identification has drawn massive attention in recent years due to its extensive applications in video surveillance.
