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Fine-Grained Visual Categorization
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SIM-OFE: Structure Information Mining and Object-aware Feature Enhancement for Fine-Grained Visual Categorization
EIANet: A Novel Domain Adaptation Approach to Maximize Class Distinction with Neural Collapse Principles
Fine-Grained Classification for Poisonous Fungi Identification with Transfer Learning
Novel Class Discovery for Ultra-Fine-Grained Visual Categorization
Data-free Knowledge Distillation for Fine-grained Visual Categorization
Context-Semantic Quality Awareness Network for Fine-Grained Visual Categorization
Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models
ViTree: Single-path Neural Tree for Step-wise Interpretable Fine-grained Visual Categorization
Cross-Level Multi-Instance Distillation for Self-Supervised Fine-Grained Visual Categorization
Learning Contrastive Self-Distillation for Ultra-Fine-Grained Visual Categorization Targeting Limited Samples
Detail Reinforcement Diffusion Model: Augmentation Fine-Grained Visual Categorization in Few-Shot Conditions
Coping with Change: Learning Invariant and Minimum Sufficient Representations for Fine-Grained Visual Categorization
Concept Drift and Long-Tailed Distribution in Fine-Grained Visual Categorization: Benchmark and Method
Incremental Generalized Category Discovery
Cross-layer Attention Network for Fine-grained Visual Categorization
SIM-Trans: Structure Information Modeling Transformer for Fine-grained Visual Categorization
Exploring Fine-Grained Audiovisual Categorization with the SSW60 Dataset
On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition
Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification
R2-Trans:Fine-Grained Visual Categorization with Redundancy Reduction
Fine-Grained Adversarial Semi-supervised Learning
A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization
Mask-Guided Feature Extraction and Augmentation for Ultra-Fine-Grained Visual Categorization
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Feature Fusion Vision Transformer for Fine-Grained Visual Categorization
Self-Supervised Learning for Fine-Grained Visual Categorization
VeriMedi: Pill Identification using Proxy-based Deep Metric Learning and Exact Solution
Benchmarking Representation Learning for Natural World Image Collections
Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization
Facing the Hard Problems in FGVC
FenceMask: A Data Augmentation Approach for Pre-extracted Image Features
TOAN: Target-Oriented Alignment Network for Fine-Grained Image Categorization with Few Labeled Samples
ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification
Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.