| Paper Abstract and Keywords |
| Presentation |
2026-02-19 15:15
Experimental Discussion on Semantic Segmentation of 3D CG Images Considering Zero-shot Learning
Norifumi Kawabata (Kanazawa Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Much research has been conducted on zero-shot learning, a type of machine learning where AI models are trained to recognize and classify objects and concepts without being shown examples of those categories or concepts beforehand. On the other hand, there were previous studies on region of interest estimation and semantic segmentation in 3D CG images. Regarding region of interest estimation in 3D CG images, it was possible to classify them using saliency maps. However, in semantic segmentation, it is a media processing technique requiring prior information. This approach has the drawback that accuracy decreases if the prior information is insufficient, or even if it is sufficient, if the categories are biased. Therefore, in this study, we considered performing semantic segmentation on 3D CG images with zero-shot learning in mind. We experimentally investigated whether classification was possible by processing based on the created architecture. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Zero-shot Learning / Contrastive Language-Image Pretraining / Label Prediction / Dense Prediction Transformer / Depth Estimation / Data Mining / / |
| Reference Info. |
ITE Tech. Rep., vol. 50, no. 5, ME2026-15, pp. 64-69, Feb. 2026. |
| Paper # |
ME2026-15 |
| 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) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
|
| Paper Information |
| Registration To |
ME |
| Conference Code |
2026-02-IE-ITS-MMS-ME-AIT-SIP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Experimental Discussion on Semantic Segmentation of 3D CG Images Considering Zero-shot Learning |
| Sub Title (in English) |
|
| Keyword(1) |
Zero-shot Learning |
| Keyword(2) |
Contrastive Language-Image Pretraining |
| Keyword(3) |
Label Prediction |
| Keyword(4) |
Dense Prediction Transformer |
| Keyword(5) |
Depth Estimation |
| Keyword(6) |
Data Mining |
| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Norifumi Kawabata |
| 1st Author's Affiliation |
Kanazawa University (Kanazawa Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2026-02-19 15:15:00 |
| Presentation Time |
15 minutes |
| Registration for |
ME |
| Paper # |
MMS2026-15, ME2026-15, AIT2026-15, SIP2026-15 |
| Volume (vol) |
vol.50 |
| Number (no) |
no.5 |
| Page |
pp.64-69 |
| #Pages |
6 |
| Date of Issue |
2026-02-12 (MMS, ME, AIT, SIP) |