多智能体协同视觉语言模型，革新PET医学影像去噪新路径
arXiv:2608.13791v1 Announce Type: cross Abstract: Positron emission tomography (PET) imaging suffers from limited spatial resolution and low signal-to…
用隐式神经表示给散斑噪声做“大扫除”，9页9图带你解锁高精度去噪新姿势。
arXiv:2608.06574v1 Announce Type: cross Abstract: Speckle fundamentally limits coherent imaging by introducing multiplicative, spatially correlated no…
核量子效应被重新定义为去噪问题，为量子计算提供全新理论视角。
arXiv:2607.19680v1 Announce Type: cross Abstract: Nuclear quantum effects are rigorously captured by imaginary-time path integrals, which map the quan…
通过聚类引导去噪平滑为LLM鲁棒性提供形式化认证，为AI安全理论注入新思路
arXiv:2512.08967v2 Announce Type: replace Abstract: Recent advancements in Large Language Models (LLMs) have led to their widespread adoption in daily…
层次贝叶斯众包模型，融合项目难度与标注者偏差，精准校正噪声标签。
arXiv:2405.19521v3 Announce Type: replace Abstract: In applied statistics and machine learning, the gold standards used for training are often biased …
联合处理颜色与偏振图像噪声、马赛克，ICIP2026新网络CPDDNet实现高质量重建。
arXiv:2607.01100v1 Announce Type: new Abstract: Color-polarization imaging using a color-polarization filter array (CPFA) sensor captures both texture…
面对被污染的观测数据，如何训练出干净的扩散模型？这篇论文给出了基于EM算法的全新方案，为生成模型在噪声场景下的应用打开了新思路。
arXiv:2407.01014v2 Announce Type: replace Abstract: Diffusion models excel in solving imaging inverse problems due to their ability to model complex i…
热红外图像去噪新算法TIDY，巧用小波域熵与方向条纹指数精准消除条纹噪声，计算机视觉方向值得一读的干货论文。
arXiv:2606.19813v1 Announce Type: cross Abstract: Thermal infrared (TIR) imaging has been a popular choice for field robotics due to its robust percep…
多模态先验注入表示空间去噪，RepFusion实现更鲁棒的跨模态表征融合。
arXiv:2606.14700v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in text-to-image (T2I) systems, but they are typically li…
一键直达最新AI论文，免费阅读全文并获取开源代码，支持版本追踪和PDF下载
arXiv:2605.08116v2 Announce Type: replace-cross Abstract: Recent work on text diffusion models offers a promising alternative to autoregressive genera…
去噪Transformer与熵编码结合，突破有损文本压缩瓶颈，兼顾压缩率与语义保留。
arXiv:2606.08184v1 Announce Type: new Abstract: Lossy text compression reduces data size while preserving core meaning, making it well-suited for summ…
融合几何感知与表征去噪，提升多视图3D重建鲁棒性，突破噪声干扰瓶颈。
arXiv:2605.26230v1 Announce Type: new Abstract: Multi-view 3D reconstruction has achieved remarkable progress with the advent of feed-forward 3D recon…
不用重新训练，直接调用预训练RGB去噪器就能修复高光谱图像，省时省成本
arXiv:2605.24769v1 Announce Type: cross Abstract: Hyperspectral image restoration faces several challenges, including limited training data, strong se…
将去噪机制融入强化学习反馈，新方法可能提升训练效率与稳定性。
arXiv:2605.25638v1 Announce Type: cross Abstract: Policy loss estimation remains a fundamental and long-standing challenge in reinforcement learning (…
零样本图学习新突破：自适应子图去噪结合大语言模型，告别一刀切，显著提升传统GNN泛化能力
arXiv:2603.02938v2 Announce Type: replace-cross Abstract: Graph-based tasks in the zero-shot setting remain a significant challenge due to data scarci…
面向大语言模型的信息检索新视角，首次提出以去噪为核心，提升检索质量与鲁棒性
arXiv:2605.00505v2 Announce Type: replace-cross Abstract: Modern information retrieval (IR) is no longer consumed primarily by humans but increasingly…
用深度学习去噪技术提升AI心电图分析精度，论文解读最新方法
arXiv:2605.03183v2 Announce Type: replace Abstract: Evaluating canine electrocardiograms (ECGs) is challenging due to noise that can obscure clinicall…
提出归一化等变性的结构先验，可应用于任意骨干网络的图像去噪，有效提升分布偏移健壮性。
arXiv:2605.08193v2 Announce Type: replace-cross Abstract: Normalization Equivariance (NE) is a structural prior that improves robustness to distributi…
用神经网络实时去除头发渲染中的噪点，大幅提升动画与游戏画质。
arXiv:2605.17557v1 Announce Type: cross Abstract: We propose a lightweight real-time method for reconstructing strand-based hair G-Buffers from severe…
提出自适应双阶段ROF去噪模型，突破经典方法对非均匀噪声的局限，理论新颖性强
arXiv:2510.04382v2 Announce Type: replace-cross Abstract: Even though more than 30 years have passed since the seminal Rudin--Osher--Fatemi (ROF) pape…