论文《Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning》来自ICLR 2024。这篇论文提出 Attention-guided COntrastive Role representation learning for MARL(ACORM),通过注意力机制学习一种更加紧凑的智能体角色表示,使得具有相似角色的智能体能够通过知识转移获得更高的学习效率,并且...
ACORM(Attention-guided COntrastive Role Representations learning for MARL)是一种新颖的多智能体强化学习框架,通过学习和利用角色表征来促进代理间的行为异质性、知识转移和熟练协调。 关键组件 1. 角色表征对比学习 将角色表征学习形式化为互信息最大化; 使用带有 InfoNCE 损失的对比学习来优化角色表征; 定期聚类智能...
Low-light images enhancement/暗光/低光/微光增强系列:Attention-guided Low-light Image Enhancement(详解) 技术标签:人工智能计算机视觉深度学习神经网络机器学习 以下文字为博主翻译并添加了自己的理解,斜体为博主自己的想法,若有出错请指出。 摘要 暗光图像增强需要同时有效地处理颜色、亮度、对比度、伪影和噪声等多...
此外,the finer relationship is established by the attention between the processed feature map Spam and the generated FG segmentation mask Proi, which can be formulated as Spam ⊗ Proi。详细信息将在下一节中进行调查。 3.3. Attention-guided Modules 考虑到 FG things与 BG stuff之间的互补关系, 我...
Attention-guided generator 上面已经介绍了整个pipeline,这里就再来看他们的生成器。 最终的s'由两部分组成,转换到T域的前景和原图s的背景。 Attention network在公式1中起到了非常重要的作用,如果Attention map Sa为全1,相当于Attention 了整个图像,那么整个工作就和CycleGAN一样了,如果Sa为全0那么所有生成的图像都会...
几篇论文实现代码:《Attention-Guided Hierarchical Structure Aggregation for Image Matting》(CVPR 2020) GitHub:http://t.cn/A6zS3oi3 《Blurry Video Frame Interpolation》(CVPR 2020) GitHub:http://t.c...
In this paper, we introduce an Attention-guided multi-Modal and multi-Scale Fusion (AMSF) module to simultaneously sample complementary local features scattered in multi-modal and multi-scale layers, and adaptively aggregate them with fine-grained attention to fully exploit different modalities for ...
Attention-Guided Hierarchical Structure Aggregation for Image Matting Abstract 现有的基于深度学习的抠图算法主要依靠高级语义特征来改善alpha mattes的整体结构,作者认为应该将高级语义信息与低级外观线索相协调,以细化前景细节 提出一种端到端的分层注意力抠图网络(HAttMatting),它可以在没有额外输入的情况... ...
To identify changes in high resolution remote sensing images, this research proposes an unique Attention-Guided Siamese Network (SAGNet). In this network, bitemporal images’ highly representative deep semantic features are retrieved using a fully convolutional dual-stream architecture, and the extracted...
We propose a deep learning system for attention-guided dual-layer image compression (AGDL). In the AGDL compression system, an image is encoded into two layers, a base layer and an attention-guided refinement layer. Unlike the existing ROI image compression methods that spend an extra bit bud...