{"id":62431,"date":"2025-04-10T20:55:37","date_gmt":"2025-04-10T20:55:37","guid":{"rendered":""},"modified":"2025-04-10T20:55:37","modified_gmt":"2025-04-10T20:55:37","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62431","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-62431\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0642\u0637\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f\u06cc \u0628\u0631 \u0627\u0633\u0627\u0633 \u0645\u062f\u0644 \u0627\u0646\u062a\u0634\u0627\u0631"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nGenerative Dataset Distillation Based on Diffusion Model<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0642\u0637\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f\u06cc \u0628\u0631 \u0627\u0633\u0627\u0633 \u0645\u062f\u0644 \u0627\u0646\u062a\u0634\u0627\u0631<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nDuo Su, Junjie Hou, Guang Li, Ren Togo, Rui Song, Takahiro Ogawa, Miki Haseyama<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u062a\u062d\u0648\u06cc\u0644\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 <\/td>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 <\/td>\n\u062f\u0648 \u062a\u0627 \u0633\u0647 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 (\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc)<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n12<\/td>\n<\/tr>\n
\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n\u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647<\/a><\/td>\n<\/tr>\n
\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nComputer Vision and Pattern Recognition,Artificial Intelligence,Machine Learning,\u0686\u0634\u0645 \u0627\u0646\u062f\u0627\u0632 \u0631\u0627\u06cc\u0627\u0646\u0647 \u0648 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0644\u06af\u0648\u06cc , \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 16 August, 2024; originally announced August 2024. , Comments: The Third Place Winner in Generative Track of the ECCV 2024 DD Challenge<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 16 \u0627\u0648\u062a 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0627\u0648\u062a 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f. \u060c \u0646\u0638\u0631\u0627\u062a: \u0628\u0631\u0646\u062f\u0647 \u0645\u0642\u0627\u0645 \u0633\u0648\u0645 \u062f\u0631 \u0622\u0647\u0646\u06af \u062a\u0648\u0644\u06cc\u062f\u06cc ECCV 2024 DD Challenge<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

This paper presents our method for the generative track of The First Dataset Distillation Challenge at ECCV 2024. Since the diffusion model has become the mainstay of generative models because of its high-quality generative effects, we focus on distillation methods based on the diffusion model. Considering that the track can only generate a fixed number of images in 10 minutes using a generative model for CIFAR-100 and Tiny-ImageNet datasets, we need to use a generative model that can generate images at high speed. In this study, we proposed a novel generative dataset distillation method based on Stable Diffusion. Specifically, we use the SDXL-Turbo model which can generate images at high speed and quality. Compared to other diffusion models that can only generate images per class (IPC) = 1, our method can achieve an IPC = 10 for Tiny-ImageNet and an IPC = 20 for CIFAR-100, respectively. Additionally, to generate high-quality distilled datasets for CIFAR-100 and Tiny-ImageNet, we use the class information as text prompts and post data augmentation for the SDXL-Turbo model. Experimental results show the effectiveness of the proposed method, and we achieved third place in the generative track of the ECCV 2024 DD Challenge. Codes are available at https:\/\/github.com\/Guang000\/BANKO.<\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n

\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0631\u0648\u0634 \u0645\u0627 \u0628\u0631\u0627\u06cc \u0622\u0647\u0646\u06af \u062a\u0648\u0644\u06cc\u062f\u06cc \u0627\u0648\u0644\u06cc\u0646 \u0686\u0627\u0644\u0634 \u062a\u0642\u0637\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0631 ECCV 2024 \u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a. \u0627\u0632 \u0622\u0646\u062c\u0627 \u06a9\u0647 \u0645\u062f\u0644 \u0627\u0646\u062a\u0634\u0627\u0631 \u0628\u0647 \u062f\u0644\u06cc\u0644 \u0627\u062b\u0631\u0627\u062a \u062a\u0648\u0644\u06cc\u062f\u06cc \u0628\u0627 \u06a9\u06cc\u0641\u06cc\u062a \u0628\u0627\u0644\u0627 \u060c \u0628\u0647 \u0627\u0635\u0644\u06cc \u062a\u0631\u06cc\u0646 \u0645\u062f\u0644 \u0647\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0647 \u0627\u0633\u062a \u060c \u0645\u0627 \u0628\u0631 \u0631\u0648\u06cc \u0631\u0648\u0634 \u0647\u0627\u06cc \u062a\u0642\u0637\u06cc\u0631 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u0645\u062f\u0644 \u0627\u0646\u062a\u0634\u0627\u0631 \u062a\u0645\u0631\u06a9\u0632 \u0645\u06cc \u06a9\u0646\u06cc\u0645.\u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0627\u06cc\u0646\u06a9\u0647 \u0627\u06cc\u0646 \u0622\u0647\u0646\u06af \u0641\u0642\u0637 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u06a9 \u0645\u062f\u0644 \u062a\u0648\u0644\u06cc\u062f\u06cc \u0628\u0631\u0627\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc Cifar-100 \u0648 Tiny-Imagenet \u060c \u062a\u0639\u062f\u0627\u062f \u0645\u0634\u062e\u0635\u06cc \u0627\u0632 \u062a\u0635\u0627\u0648\u06cc\u0631 \u0631\u0627 \u062f\u0631 10 \u062f\u0642\u06cc\u0642\u0647 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u062f \u060c \u0645\u0627 \u0628\u0627\u06cc\u062f \u0627\u0632 \u06cc\u06a9 \u0645\u062f\u0644 \u062a\u0648\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645 \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0627 \u0633\u0631\u0639\u062a \u0628\u0627\u0644\u0627 \u062a\u0635\u0627\u0648\u06cc\u0631 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u062f.\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u060c \u0645\u0627 \u06cc\u06a9 \u0631\u0648\u0634 \u062a\u0642\u0637\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f\u06cc \u062c\u062f\u06cc\u062f \u0631\u0627 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0627\u0646\u062a\u0634\u0627\u0631 \u067e\u0627\u06cc\u062f\u0627\u0631 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f \u06a9\u0631\u062f\u06cc\u0645.\u0628\u0647 \u0637\u0648\u0631 \u062e\u0627\u0635 \u060c \u0645\u0627 \u0627\u0632 \u0645\u062f\u0644 SDXL-Turbo \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062a\u0635\u0627\u0648\u06cc\u0631 \u0631\u0627 \u0628\u0627 \u0633\u0631\u0639\u062a \u0648 \u06a9\u06cc\u0641\u06cc\u062a \u0628\u0627\u0644\u0627 \u062a\u0648\u0644\u06cc\u062f \u06a9\u0646\u062f.\u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 \u0633\u0627\u06cc\u0631 \u0645\u062f\u0644 \u0647\u0627\u06cc \u0627\u0646\u062a\u0634\u0627\u0631 \u06a9\u0647 \u0641\u0642\u0637 \u0645\u06cc \u062a\u0648\u0627\u0646\u0646\u062f \u062f\u0631 \u0647\u0631 \u06a9\u0644\u0627\u0633 \u062a\u0635\u0627\u0648\u06cc\u0631 (IPC) = 1 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u0646\u062f \u060c \u0631\u0648\u0634 \u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0647 \u062a\u0631\u062a\u06cc\u0628 IPC = 10 \u0631\u0627 \u0628\u0631\u0627\u06cc Imagenet \u06a9\u0648\u0686\u06a9 \u0648 IPC = 20 \u0628\u0631\u0627\u06cc CIFAR-100 \u0628\u0647 \u062f\u0633\u062a \u0622\u0648\u0631\u062f.\u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646 \u060c \u0628\u0631\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0642\u0637\u0631 \u0628\u0627 \u06a9\u06cc\u0641\u06cc\u062a \u0628\u0627\u0644\u0627 \u0628\u0631\u0627\u06cc CIFAR-100 \u0648 Imagenet Tiny \u060c \u0645\u0627 \u0627\u0632 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u06a9\u0644\u0627\u0633 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062a\u0646 \u0645\u062a\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0648 \u0627\u0641\u0632\u0627\u06cc\u0634 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u062f\u0644 SDXL \u062a\u0648\u0631\u0628\u0648 \u0627\u0631\u0633\u0627\u0644 \u0645\u06cc \u06a9\u0646\u06cc\u0645.\u0646\u062a\u0627\u06cc\u062c \u062a\u062c\u0631\u0628\u06cc \u0627\u062b\u0631\u0628\u062e\u0634\u06cc \u0631\u0648\u0634 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f\u06cc \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u060c \u0648 \u0645\u0627 \u062f\u0631 \u0645\u0633\u06cc\u0631 \u062a\u0648\u0644\u06cc\u062f\u06cc \u0686\u0627\u0644\u0634 ECCV 2024 DD \u0628\u0647 \u0645\u0642\u0627\u0645 \u0633\u0648\u0645 \u0631\u0633\u06cc\u062f\u06cc\u0645.\u06a9\u062f\u0647\u0627 \u062f\u0631 https:\/\/github.com\/guang000\/banko \u062f\u0631 \u062f\u0633\u062a\u0631\u0633 \u0647\u0633\u062a\u0646\u062f.<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
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