{"total":19,"rows":[{"id":"2303.04803","title":"Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models","created":"2023-03-08","cited_by_count":375,"area":"diffusion"},{"id":"2211.09788","title":"DiffusionDet: Diffusion Model for Object Detection","created":"2022-11-17","cited_by_count":354,"area":"diffusion"},{"id":"2303.17189","title":"LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation","created":"2023-03-30","cited_by_count":259,"area":"diffusion"},{"id":"2407.00783","title":"Diffusion Models and Representation Learning: A Survey","created":"2024-06-30","cited_by_count":54,"area":"diffusion"},{"id":"2309.00810","title":"RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model","created":"2023-09-02","cited_by_count":47,"area":"diffusion"},{"id":"2411.11505","title":"LaVin-DiT: Large Vision Diffusion Transformer","created":"2024-11-18","cited_by_count":21,"area":"diffusion"},{"id":"2303.14863","title":"DiffTAD: Temporal Action Detection with Proposal Denoising Diffusion","created":"2023-03-27","cited_by_count":19,"area":"diffusion"},{"id":"2312.05039","title":"SmartMask: Context Aware High-Fidelity Mask Generation for Fine-grained Object Insertion and Layout Control","created":"2023-12-08","cited_by_count":18,"area":"diffusion"},{"id":"2401.10227","title":"A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting","created":"2024-01-18","cited_by_count":18,"area":"diffusion"},{"id":"2412.10783","title":"Video Diffusion Transformers are In-Context Learners","created":"2024-12-14","cited_by_count":12,"area":"diffusion"},{"id":"2408.00286","title":"Diff3DETR:Agent-based Diffusion Model for Semi-supervised 3D Object Detection","created":"2024-08-01","cited_by_count":7,"area":"diffusion"},{"id":"2601.05241","title":"RoboVIP: Multi-View Video Generation with Visual Identity Prompting Augments Robot Manipulation","created":"2026-01-08","cited_by_count":7,"area":"diffusion"},{"id":"2403.13652","title":"ZoDi: Zero-Shot Domain Adaptation with Diffusion-Based Image Transfer","created":"2024-03-20","cited_by_count":5,"area":"diffusion"},{"id":"2503.12507","title":"Segment Any-Quality Images with Generative Latent Space Enhancement","created":"2025-03-16","cited_by_count":3,"area":"diffusion"},{"id":"2602.18589","title":"DM4CT: Benchmarking Diffusion Models for Computed Tomography Reconstruction","created":"2026-02-20","cited_by_count":3,"area":"diffusion"},{"id":"2312.01682","title":"ResEnsemble-DDPM: Residual Denoising Diffusion Probabilistic Models for Ensemble Learning","created":"2023-12-04","cited_by_count":0,"area":"diffusion"},{"id":"2407.14326","title":"Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model","created":"2024-07-19","cited_by_count":0,"area":"diffusion"},{"id":"2412.02929","title":"Panoptic Diffusion Models: co-generation of images and segmentation maps","created":"2024-12-04","cited_by_count":0,"area":"diffusion"},{"id":"2610.00483","title":"PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion","created":"2026-09-30","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}