Delving into multimodal prompting for fine-grained visual classification
Fine-grained visual classification (FGVC) involves categorizing fine subdivisions within a broader category, which poses challenges due to subtle inter-class discrepancies and large intra-class variations. However, prevailing approaches primarily focus on uni-modal visual concepts. Recent advancemen...
Saved in:
Main Authors: | JIANG, Xin, TANG, Hao, GAO, Junyao, DU, Xiaoyu, HE, Shengfeng, LI, Zechao |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/8741 https://ink.library.smu.edu.sg/context/sis_research/article/9744/viewcontent/28034_Article_Text_32088_1_2_20240324.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Few-shot fine-grained classification with Spatial Attentive Comparison
by: Ruan, Xiaoqian, et al.
Published: (2022) -
Fine-grained and controllably redactable blockchain with harmful data forced removal
by: HOU, Huiying, et al.
Published: (2021) -
NEURAL FINE-GRAINED SENTIMENT ANALYSIS WITH UNSUPERVISED AND TRANSFER LEARNING APPROACHES
by: HE RUIDAN
Published: (2020) -
Hierarchical part matching for fine-grained visual categorization
by: Xie, L., et al.
Published: (2014) -
Automatic Fine-Grained Issue Report Reclassification
by: Kochhar, Pavneet Singh, et al.
Published: (2014)