Browse SoTA > Computer Vision > Image Classification > Fine-Grained Image Classification

Fine-Grained Image Classification

37 papers with code · Computer Vision

The Fine-Grained Image Classification task focuses on differentiating between hard-to-distinguish object classes, such as species of birds, flowers, or animals; and identifying the makes or models of vehicles.

( Image credit: Looking for the Devil in the Details )

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Latest papers with code

ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks

26 Jun 2020Nandan91/ULSAM

Our method of subspace attention is orthogonal and complementary to the existing state-of-the-arts attention mechanisms used in vision models.

FINE-GRAINED IMAGE CLASSIFICATION

4
26 Jun 2020

Learning Semantically Enhanced Feature for Fine-Grained Image Classification

24 Jun 2020cswluo/SEF

We aim to provide a computationally cheap yet effective approach for fine-grained image classification (FGIC) in this letter.

FINE-GRAINED IMAGE CLASSIFICATION

4
24 Jun 2020

Focus Longer to See Better:Recursively Refined Attention for Fine-Grained Image Classification

22 May 2020TAMU-VITA/Focus-Longer-to-See-Better

In this paper, we tried to focus on these marginal differences to extract more representative features.

FINE-GRAINED IMAGE CLASSIFICATION

10
22 May 2020

Neural Architecture Transfer

12 May 2020human-analysis/neural-architecture-transfer

At the same time, the architecture search and transfer is orders of magnitude more efficient than existing NAS methods.

FINE-GRAINED IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH TRANSFER LEARNING

45
12 May 2020

Gradient Centralization: A New Optimization Technique for Deep Neural Networks

3 Apr 2020lessw2020/Ranger-Deep-Learning-Optimizer

It has been shown that using the first and second order statistics (e. g., mean and variance) to perform Z-score standardization on network activations or weight vectors, such as batch normalization (BN) and weight standardization (WS), can improve the training performance.

FINE-GRAINED IMAGE CLASSIFICATION

667
03 Apr 2020

Look-into-Object: Self-supervised Structure Modeling for Object Recognition

CVPR 2020 JDAI-CV/DCL

Specifically, we first propose an object-extent learning module for localizing the object according to the visual patterns shared among the instances in the same category.

FINE-GRAINED IMAGE CLASSIFICATION OBJECT DETECTION OBJECT RECOGNITION REPRESENTATION LEARNING

351
31 Mar 2020

Proxy Anchor Loss for Deep Metric Learning

CVPR 2020 tjddus9597/Proxy-Anchor-CVPR2020

The former class can leverage fine-grained semantic relations between data points, but slows convergence in general due to its high training complexity.

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED VEHICLE CLASSIFICATION METRIC LEARNING

88
31 Mar 2020

TResNet: High Performance GPU-Dedicated Architecture

30 Mar 2020rwightman/pytorch-image-models

In this work, we introduce a series of architecture modifications that aim to boost neural networks' accuracy, while retaining their GPU training and inference efficiency.

FINE-GRAINED IMAGE CLASSIFICATION MULTI-LABEL CLASSIFICATION OBJECT DETECTION

4,169
30 Mar 2020

Three-branch and Mutil-scale learning for Fine-grained Image Recognition (TBMSL-Net)

20 Mar 2020ZF1044404254/TBMSL-Net

ImageNet Large Scale Visual Recognition Challenge (ILSVRC) is one of the most authoritative academic competitions in the field of Computer Vision (CV) in recent years, but it can not achieve good result to directly migrate the champions of the annual competition, to fine-grained visual categorization (FGVC) tasks.

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED IMAGE RECOGNITION FINE-GRAINED VISUAL CATEGORIZATION OBJECT RECOGNITION

37
20 Mar 2020