To mitigate this, we propose the simple and effective Semantic-aware Discriminator (denoted as SeD), which encourages the SR network to learn the fine-grained distributions by introducing the semantics of images as a condition. Concretely, we aim to excavate the semantics of imag...
Semantic-Aware Discriminator for Image Super-Resolution This repository is the official PyTorch implementation of SeD: Semantic-Aware Discriminator for Image Super-Resolution (CVPR24) 🔖 News!!! 2024-3-24: Updated training codes! 2024-4-11: Updated test codes and U+SeD. Generative Adversarial Ne...
增加了Zs和Zt的输入 输出使用Discriminator计算损失 而这个网络结构不是凭空提出来的,是借鉴了这些相关工作: 2.1 GRAF(Generative Radiance Fields for 3D-Aware Image Synthesis) 重点: 1.一个标准的conditional GAN, 然后NeRF的部分就放在了生成器里面。 2.生成器的输入是相机的参数(位置,方向,焦点,远近等等),这些...
We re-design the discriminator as a semantic segmentation network, directly using the given semantic label maps as the ground truth for training. By providing stronger supervision to the discriminator as well as to the generator through spatially- and semantically-aware discriminator feedback, we are...
Specifically, the ability of the discriminator is improved by using segmen- tation map to determine the fake areas, which can improve the image quality further. The main contributions of our work are as follows: • We propose a semantic-aware knowledge-guided f...
Learning Discriminators as Energy Networks in Adversarial Learning 2018 [paper]Learning to Segment via Cut-and-Paste ECCV 2018 [paper]Leveraging Motion Priors in Videos for Improving Human Segmentation ECCV 2018 [paper]Light-Weight RefineNet for Real-Time Semantic Segmentation BMVC 2018 [paper]...
(GANs), research has primarily focused on addressing the issue of GANs fusing only partial information from source images and enhancing information in fused images. Source images of different modalities possess distinct feature information. The competition between a single generator and discriminator could...
[56] generates images through the zero-sum game between the generator and discriminator, producing images with highly similar syntactic information to real images. Similar to the semantic representation and coding for text and audio sources, DL-based semantic feature extractions and joint source-...
The Minimax Active Learning (MAL) framework also used a discriminator to classify the most diverse samples as compared to the labeled set and paired it with class prototypes to identify the highest en- tropy samples [21]. The Difficulty-awarE Active Learn- ing (DEAL) a...
DANES: Deep neural network ensemble architecture for social and textual context-aware fake news detection (2023) arXiv preprint arXiv:2302.01756 Google Scholar Van der Maaten and Hinton, 2008 Van der Maaten L., Hinton G. Visualizing data using t-SNE J. Mach. Learn. Res., 9 (11) (2008)...