{"total":45,"rows":[{"id":"2112.00390","title":"SegDiff: Image Segmentation with Diffusion Probabilistic Models","created":"2021-12-01","cited_by_count":280,"area":"diffusion"},{"id":"2303.17559","title":"DDP: Diffusion Model for Dense Visual Prediction","created":"2023-03-30","cited_by_count":148,"area":"diffusion"},{"id":"2306.13754","title":"Zero-shot spatial layout conditioning for text-to-image diffusion models","created":"2023-06-23","cited_by_count":64,"area":"diffusion"},{"id":"2407.00783","title":"Diffusion Models and Representation Learning: A Survey","created":"2024-06-30","cited_by_count":54,"area":"diffusion"},{"id":"2403.16605","title":"SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation","created":"2024-03-25","cited_by_count":41,"area":"diffusion"},{"id":"2303.08888","title":"Stochastic Segmentation with Conditional Categorical Diffusion Models","created":"2023-03-15","cited_by_count":38,"area":"diffusion"},{"id":"2303.18080","title":"One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models","created":"2023-03-31","cited_by_count":35,"area":"diffusion"},{"id":"2211.13224","title":"Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors","created":"2022-11-23","cited_by_count":34,"area":"diffusion"},{"id":"2307.16579","title":"Contrastive Conditional Latent Diffusion for Audio-visual Segmentation","created":"2023-07-31","cited_by_count":31,"area":"diffusion"},{"id":"2307.02138","title":"Prompting Diffusion Representations for Cross-Domain Semantic Segmentation","created":"2023-07-05","cited_by_count":30,"area":"diffusion"},{"id":"2312.01985","title":"UniGS: Unified Representation for Image Generation and Segmentation","created":"2023-12-04","cited_by_count":29,"area":"diffusion"},{"id":"2304.05961","title":"SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Models","created":"2023-04-12","cited_by_count":28,"area":"diffusion"},{"id":"2308.12350","title":"Diffusion-based Image Translation with Label Guidance for Domain Adaptive Semantic Segmentation","created":"2023-08-23","cited_by_count":27,"area":"diffusion"},{"id":"2303.09604","title":"DS-Fusion: Artistic Typography via Discriminated and Stylized Diffusion","created":"2023-03-16","cited_by_count":26,"area":"diffusion"},{"id":"2308.13767","title":"DiffI2I: Efficient Diffusion Model for Image-to-Image Translation","created":"2023-08-26","cited_by_count":24,"area":"diffusion"},{"id":"2302.12764","title":"Modulating Pretrained Diffusion Models for Multimodal Image Synthesis","created":"2023-02-24","cited_by_count":23,"area":"diffusion"},{"id":"2405.20282","title":"SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow","created":"2024-05-30","cited_by_count":20,"area":"diffusion"},{"id":"2309.04109","title":"From Text to Mask: Localizing Entities Using the Attention of Text-to-Image Diffusion Models","created":"2023-09-08","cited_by_count":16,"area":"diffusion"},{"id":"2503.09344","title":"Unified Dense Prediction of Video Diffusion","created":"2025-03-12","cited_by_count":13,"area":"diffusion"},{"id":"2405.10550","title":"LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion","created":"2024-05-17","cited_by_count":12,"area":"diffusion"},{"id":"2409.03209","title":"iSeg: An Iterative Refinement-based Framework for Training-free Segmentation","created":"2024-09-05","cited_by_count":10,"area":"diffusion"},{"id":"2309.16318","title":"DeepPCR: Parallelizing Sequential Operations in Neural Networks","created":"2023-09-28","cited_by_count":9,"area":"diffusion"},{"id":"2507.22459","title":"Exploiting Diffusion Prior for Task-driven Image Restoration","created":"2025-07-30","cited_by_count":8,"area":"diffusion"},{"id":"2312.13314","title":"Unlocking Pre-trained Image Backbones for Semantic Image Synthesis","created":"2023-12-20","cited_by_count":6,"area":"diffusion"},{"id":"2604.15521","title":"Frequency-Aware Flow Matching for High-Quality Image Generation","created":"2026-04-16","cited_by_count":6,"area":"diffusion"},{"id":"2212.14306","title":"Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models","created":"2022-12-29","cited_by_count":5,"area":"diffusion"},{"id":"2310.03664","title":"Certification of Deep Learning Models for Medical Image Segmentation","created":"2023-10-05","cited_by_count":5,"area":"diffusion"},{"id":"2311.17121","title":"ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic Segmentation","created":"2023-11-28","cited_by_count":5,"area":"diffusion"},{"id":"2506.01539","title":"G4Seg: Generation for Inexact Segmentation Refinement with Diffusion Models","created":"2025-06-02","cited_by_count":5,"area":"diffusion"},{"id":"2507.19808","title":"SeeDiff: Off-the-Shelf Seeded Mask Generation from Diffusion Models","created":"2025-07-26","cited_by_count":5,"area":"diffusion"},{"id":"2512.16636","title":"REGLUE Your Latents with Global and Local Semantics for Entangled Diffusion","created":"2025-12-18","cited_by_count":5,"area":"diffusion"},{"id":"2410.21638","title":"Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis","created":"2024-10-29","cited_by_count":4,"area":"diffusion"},{"id":"2404.07600","title":"Implicit and Explicit Language Guidance for Diffusion-based Visual Perception","created":"2024-04-11","cited_by_count":3,"area":"diffusion"},{"id":"2406.00210","title":"A-SDM: Accelerating Stable Diffusion through Model Assembly and Feature Inheritance Strategies","created":"2024-05-31","cited_by_count":3,"area":"diffusion"},{"id":"2501.10548","title":"Diffusion Models in Recommendation Systems: A Survey","created":"2025-01-17","cited_by_count":3,"area":"diffusion"},{"id":"2603.14965","title":"GeoNVS: Geometry Grounded Video Diffusion for Novel View Synthesis","created":"2026-03-16","cited_by_count":3,"area":"diffusion"},{"id":"2504.17628","title":"Beyond Labels: Zero-Shot Diabetic Foot Ulcer Wound Segmentation with Self-attention Diffusion Models and the Potential for Text-Guided Customization","created":"2025-04-24","cited_by_count":1,"area":"diffusion"},{"id":"2507.15595","title":"SegDT: A Diffusion Transformer-Based Segmentation Model for Medical Imaging","created":"2025-07-21","cited_by_count":1,"area":"diffusion"},{"id":"2606.15590","title":"Unlocking Diffusion Hierarchies: Adaptive Timestep Selection for Zero-Shot Segmentation","created":"2026-06-14","cited_by_count":1,"area":"diffusion"},{"id":"2503.18170","title":"Self-Attention Diffusion Models for Zero-Shot Biomedical Image Segmentation: Unlocking New Frontiers in Medical Imaging","created":"2025-03-23","cited_by_count":0,"area":"diffusion"},{"id":"2508.06032","title":"Learning 3D Texture-Aware Representations for Parsing Diverse Human Clothing and Body Parts","created":"2025-08-08","cited_by_count":0,"area":"diffusion"},{"id":"2512.13970","title":"Quality-Driven and Diversity-Aware Sample Expansion for Robust Marine Obstacle Segmentation","created":"2025-12-16","cited_by_count":0,"area":"diffusion"},{"id":"2603.19218","title":"Rethinking Vector Field Learning for Generative Segmentation","created":"2026-03-19","cited_by_count":0,"area":"diffusion"},{"id":"2605.04593","title":"DiCLIP: Diffusion Model Enhances CLIP's Dense Knowledge for Weakly Supervised Semantic Segmentation","created":"2026-05-06","cited_by_count":0,"area":"diffusion"},{"id":"2607.25390","title":"Noise-Free One-Step LoRA for Task-Driven Image Restoration with Diffusion Priors","created":"2026-07-28","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}