Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space, and a decoder maps the generated latents back to pixels. Yet the latent-to-pixel decoder is reconstruction-oriented, optimized to invert the encoder rather than synthesize more details, and becomes increasingly costly at megapixel scale. This drawback calls for a more expressive and efficient decoding paradigm. Motivated by recent progress in scalable pixel-space diffusion, we introduce PiD, a Pixel diffusion Decoder that reformulates latent decoding as conditional pixel diffusion, unifying decoding and upsampling into one generative module. By denoising directly in high-resolution pixel space, PiD synthesizes $4\times$ and even $8\times$ upscaled images with low latency. For latent conditioning, a lightweight sigma-aware adapter injects noise-corrupted latents into the pixel diffusion backbone, enabling PiD to decode partially denoised latents and terminate the latent diffusion process early. To further improve efficiency, we distill the model using DMD2, reducing inference to just 4 steps. PiD applies to both conventional VAE latents and semantic latents (e.g., SigLIP, DINOv2) used in recent RAE-based models. PiD decodes latents of $512 \times 512$ images into $2048 \times 2048$ pixels in under 1 second with 13 GB peak memory on a consumer RTX 5090, and as fast as 210 ms on a GB200 GPU, about $6\times$ faster than cascaded diffusion-based super-resolution pipelines with better visual fidelity.
An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images
Northeastern University（东北大学）；Chengdu University of Information Technology（成都信息工程大学）；Stevens Institute of Technology（史蒂文斯理工学院）；National Chung Hsing University（中兴大学）；Huazhong University of Science and Technology（华中科技大学）；University of Luebeck（吕贝克大学）
Video Generation Models Are Good Latent Reward Models
University of Chinese Academy of Sciences（中国科学院大学）；Tencent Hunyuan（腾讯文元）；Huazhong University of Science and Technology（华中科技大学）；Peking University（北京大学）；Shanghai Jiao Tong University（上海交通大学）；Tsinghua University（清华大学）；Nanjing University（南京大学）
Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal
The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University（武汉大学测绘遥感信息工程国家重点实验室）；School of Remote Sensing and Information Engineering, Wuhan University（武汉大学遥感信息工程学院）
CoQui: A Coordinate-Conditioned Quantum Implicit Generative Adversarial Network for End-to-End Image Generation
Shanghai Maritime University（上海海事大学）；Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局）；Singapore Institute of Technology（新加坡理工学院）；Singapore Management University (SMU)（新加坡管理大学）；Tongji University（同济大学）；Tsinghua University（清华大学）
Robust Single-shot Structured Light 3D Imaging via Neural Feature Decoding
Wangxuan Institute of Computer Technology, Peking University（北京大学王轩计算机技术研究院）；School of Intelligence Science and Technology, Peking University（北京大学智能科学与技术学院）；Yuanpei College, Peking University（北京大学元培学院）；University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）；College of Future Technology, Peking University（北京大学未来技术学院）；State Key Laboratory of General Artificial Intelligence, Peking University（北京大学通用人工智能国家重点实验室）
Image-Plane Geometric Decoding for View-Invariant Indoor Scene Reconstruction
School of Microelectronics,Tianjin University（天津大学微电子学院）；College of Electronic Information and Optical Engineering,Nankai University（南开大学电子信息与光工程学院）；Technology Research Institute of MEM（MEM技术研究所）
University of Sydney（悉尼大学）；OPPO Research Institute（OPPO研究院）；Beijing University of Posts and Telecommunications（北京邮电大学）；Kuaishou Technology（快手科技）；University of Melbourne（墨尔本大学）
NCIS: Deep Color Gradient Maps Regression and Three-Class Pixel Classification for Enhanced Neuronal Cell Instance Segmentation in Nissl-Stained Histological Images
London South Bank University（伦敦南岸大学）；University of Padova（帕多瓦大学）
Pixel-Inconsistency Modeling for Image Manipulation Localization
Nanyang Technology University（南洋理工大学）；School of Electrical and Electronic Engineering（电子电气工程学院）；Rapid-Rich Object Search (ROSE) Lab（快速富对象搜索实验室）；School of Computer Science and Engineering（计算机科学与工程学院）；Sun Yat-sen University（中山大学）；City University of Hong Kong（香港城市大学）；University of Campinas（坎皮纳斯大学）；Institute of Computing（计算机研究所）；Artificial Intelligence Laboratory (Recod.ai)（人工智能实验室（Recod.ai））
RaPD: Resolution-Agnostic Pixel Diffusion via Semantics-Enriched Implicit Representations
College of Electronic and Information Engineering, Tongji University（同济大学电子与信息工程学院）；vivo Mobile Communication Co., Ltd.（vivo移动通信有限公司）；Nanjing University（南京大学）
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding
East China Normal University（华东师范大学）；Stanford University（斯坦福大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；University of Hong Kong（香港大学）；University of Florida（佛罗里达大学）；UC Santa Cruz（加州大学圣克鲁兹分校）
