NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results. | 0 | 0.34 | 2022 |
Revisiting Random Channel Pruning for Neural Network Compression | 0 | 0.34 | 2022 |
Plug-and-Play Image Restoration With Deep Denoiser Prior | 11 | 0.50 | 2022 |
Reference-Based Image Super-Resolution with Deformable Attention Transformer. | 0 | 0.34 | 2022 |
Towards Efficient Graph Convolutional Networks for Point Cloud Handling. | 0 | 0.34 | 2021 |
The Heterogeneity Hypothesis: Finding Layer-Wise Differentiated Network Architectures | 0 | 0.34 | 2021 |
Unsupervised Real-World Image Super Resolution via Domain-Distance Aware Training. | 0 | 0.34 | 2021 |
Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation | 0 | 0.34 | 2021 |
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression | 3 | 0.39 | 2020 |
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results | 1 | 0.41 | 2020 |
3d Appearance Super-Resolution With Deep Learning | 2 | 0.36 | 2019 |
Self-Guided Network For Fast Image Denoising | 10 | 0.47 | 2019 |
Modified non-local means for super-resolution of hybrid videos. | 2 | 0.37 | 2018 |
Multiview Video Super-Resolution via Information Extraction and Merging. | 2 | 0.38 | 2016 |
Joint Visual Denoising and Classification using Deep Learning. | 0 | 0.34 | 2016 |