| Paper Abstract and Keywords |
| Presentation |
2026-02-19 14:30
A Note on Object-Aware Dataset Distillation with Adaptive Patch Selection Longzhen Li, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In recent years, rapid advances in artificial intelligence have led to an increasing demand for large-scale model training, which in turn has resulted in prohibitively high computational and storage costs. Modern AI systems typically rely on massive datasets, causing substantial memory consumption and extremely long training times. Although existing dataset distillation methods aim to improve training efficiency by compressing large datasets into compact synthetic sets, they often suffer from limited image realism, complex training pipelines, and unstable optimization. In this paper, we propose a novel object-aware dataset distillation framework based on an adaptive patch selection strategy. We create patches from real images, which allows our method to maintain the visual realism of the distilled images while eliminating a significant amount of optimization work. Specifically, we leverage Grounded SAM2 to identify the primary object in each image during the distillation process, and dynamically select informative patches according to the data distribution characteristics of the original samples. The distilled data are then synthesized from these optimal patches. By explicitly preserving object-centric semantic information, our method retains more discriminative content in the distilled images. Extensive experiments demonstrate that our approach consistently achieves higher accuracy than conventional methods. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Dataset distillation / Grounded SAM2 / Adaptive patch selection / / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 50, no. 5, ME2026-12, pp. 51-54, Feb. 2026. |
| Paper # |
ME2026-12 |
| Date of Issue |
2026-02-12 (MMS, ME, AIT, SIP) |
| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IEICE-IE IEICE-ITS MMS ME AIT SIP |
| Conference Date |
2026-02-19 - 2026-02-20 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
ME |
| Conference Code |
2026-02-IE-ITS-MMS-ME-AIT-SIP |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A Note on Object-Aware Dataset Distillation with Adaptive Patch Selection |
| Sub Title (in English) |
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| Keyword(1) |
Dataset distillation |
| Keyword(2) |
Grounded SAM2 |
| Keyword(3) |
Adaptive patch selection |
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| 1st Author's Name |
Longzhen Li |
| 1st Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 2nd Author's Name |
Guang Li |
| 2nd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 3rd Author's Name |
Ren Togo |
| 3rd Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 4th Author's Name |
Keisuke Maeda |
| 4th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 5th Author's Name |
Takahiro Ogawa |
| 5th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
| 6th Author's Name |
Miki Haseyama |
| 6th Author's Affiliation |
Hokkaido University (Hokkaido Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2026-02-19 14:30:00 |
| Presentation Time |
15 minutes |
| Registration for |
ME |
| Paper # |
MMS2026-12, ME2026-12, AIT2026-12, SIP2026-12 |
| Volume (vol) |
vol.50 |
| Number (no) |
no.5 |
| Page |
pp.51-54 |
| #Pages |
4 |
| Date of Issue |
2026-02-12 (MMS, ME, AIT, SIP) |