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Physical Sciences › Computer Science › Computer Vision and Pattern Recognition
Fine-Grained Image Analysis with Deep Learning: A Survey
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Paper Summary
Paperzilla title
Fine-Grained: Teach Machines to See Like Humans, Almost!
The survey examines deep learning advancements in fine-grained image analysis (FGIA), arguing for a broader definition encompassing recognition and retrieval. It presents a taxonomy of techniques, evaluates performance on benchmarks, and outlines future research directions, including precise definition, new datasets, 3D application, robust representations, and interpretability.
Possible Conflicts of Interest
None identified
Identified Weaknesses
Precise Definition of Fine-Grained Analysis
It is mentioned that FGIA lacks a precise definition. A precise definition would be very useful for evaluating different FGIA methods and FGIA datasets and improving the research in FGIA.
Rating Explanation
This survey paper offers a valuable and insightful overview of fine-grained image analysis, covering recognition and retrieval. It tackles existing challenges and proposes future directions, making it an essential resource. The rating reflects the paper's strengths in structure, content, and importance to the field.
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Topic Hierarchy
File Information
Original Title:
Fine-Grained Image Analysis with Deep Learning: A Survey
File Name:
Fine_Grained_Image.pdf
[download]
File Size:
4.74 MB
Uploaded:
July 14, 2025 at 05:20 PM
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