Papers with Code 아카이브
Fine-Grained Image Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Cross-Layer Cache Aggregation for Token Reduction in Ultra-Fine-Grained Image Recognition
Down-Sampling Inter-Layer Adapter for Parameter and Computation Efficient Ultra-Fine-Grained Image Recognition
Enhancing Fine-Grained Visual Recognition in the Low-Data Regime Through Feature Magnitude Regularization
Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models
Global-Local Similarity for Efficient Fine-Grained Image Recognition with Vision Transformers
GCAM: Gaussian and causal-attention model of food fine-grained recognition
Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning
Dining on Details: LLM-Guided Expert Networks for Fine-Grained Food Recognition
Hawkeye: A PyTorch-based Library for Fine-Grained Image Recognition with Deep Learning
Fine-grained Recognition with Learnable Semantic Data Augmentation
Complementary Frequency-Varying Awareness Network for Open-Set Fine-Grained Image Recognition
Retrieval-Enhanced Contrastive Vision-Text Models
PaLI-X: On Scaling up a Multilingual Vision and Language Model
Application of attention-based Siamese composite neural network in medical image recognition
ELFIS: Expert Learning for Fine-grained Image Recognition Using Subsets
Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities
Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition
Learning Deep Optimal Embeddings with Sinkhorn Divergences
Taxonomy and evolution predicting using deep learning in images
Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals
A Novel Plug-in Module for Fine-Grained Visual Classification
SelectAugment: Hierarchical Deterministic Sample Selection for Data Augmentation
Full-attention based Neural Architecture Search using Context Auto-regression
Fine-Grained Image Analysis with Deep Learning: A Survey
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels
Attend and Guide (AG-Net): A Keypoints-driven Attention-based Deep Network for Image Recognition
Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand Hygiene
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Learning Canonical 3D Object Representation for Fine-Grained Recognition
RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition
Transformer with Peak Suppression and Knowledge Guidance for Fine-grained Image Recognition
Exploring Localization for Self-supervised Fine-grained Contrastive Learning
Local Patch AutoAugment with Multi-Agent Collaboration
Danish Fungi 2020 -- Not Just Another Image Recognition Dataset
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.