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Fine-Grained Image Recognition

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Showing 26–50 of 72 papers

TitleStatusHype
Fine-Grained Image Analysis with Deep Learning: A Survey—0
Fine-grained Image Classification by Exploring Bipartite-Graph Labels—0
Fine-grained Image-to-Image Transformation towards Visual Recognition—0
Full-attention based Neural Architecture Search using Context Auto-regression—0
GCAM: Gaussian and causal-attention model of food fine-grained recognition—0
Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models—0
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition—0
Learning Canonical 3D Object Representation for Fine-Grained Recognition—0
Learning Deep Optimal Embeddings with Sinkhorn Divergences—0
Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition—0
Mask-CNN: Localizing Parts and Selecting Descriptors for Fine-Grained Image Recognition—0
Open-Set Recognition of Novel Species in Biodiversity Monitoring—0
Picking Deep Filter Responses for Fine-Grained Image Recognition—0
RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition—0
REAPS: Towards Better Recognition of Fine-grained Images by Region Attending and Part Sequencing—0
Re-rank Coarse Classification with Local Region Enhanced Features for Fine-Grained Image Recognition—0
Retrieval-Enhanced Contrastive Vision-Text Models—0
SelectAugment: Hierarchical Deterministic Sample Selection for Data Augmentation—0
Siamese transformer with hierarchical concept embedding for fine-grained image recognition—0
Spatial-Temporal Attention Network for Open-Set Fine-Grained Image Recognition—0
Structural feature enhanced transformer for fine-grained image recognition—0
Text-Embedded Bilinear Model for Fine-Grained Visual Recognition—0
Transformer with Peak Suppression and Knowledge Guidance for Fine-grained Image Recognition—0
Volumetric Transformer Networks—0
Pay attention to the activations: a modular attention mechanism for fine-grained image recognitionCode0
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