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Greatest papers with code

Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization

CVPR 2018 osmr/imgclsmob

Towards addressing this problem, we propose an iterative matrix square root normalization method for fast end-to-end training of global covariance pooling networks.

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED IMAGE RECOGNITION

Semi-Supervised Recognition under a Noisy and Fine-grained Dataset

18 Jun 2020PaddlePaddle/PaddleClas

One of the difficulties of this competition is how to use unlabeled data.

Ranked #27 on Image Classification on ImageNet (using extra training data)

FINE-GRAINED IMAGE RECOGNITION IMAGE CLASSIFICATION

Destruction and Construction Learning for Fine-Grained Image Recognition

CVPR 2019 JDAI-CV/DCL

In this paper, we propose a novel "Destruction and Construction Learning" (DCL) method to enhance the difficulty of fine-grained recognition and exercise the classification model to acquire expert knowledge.

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED IMAGE RECOGNITION

Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization

20 Mar 2020ZF4444/MMAL-Net

The obtained object images not only contain almost the entire structure of the object, but also contains more details, part images have many different scales and more fine-grained features, and the raw images contain the complete object.

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

Learning Deep Bilinear Transformation for Fine-grained Image Representation

NeurIPS 2019 researchmm/DBTNet

However, the computational cost to learn pairwise interactions between deep feature channels is prohibitively expensive, which restricts this powerful transformation to be used in deep neural networks.

FINE-GRAINED IMAGE RECOGNITION

Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

14 Aug 2018HCPLab-SYSU/HSE

In this work, we investigate simultaneously predicting categories of different levels in the hierarchy and integrating this structured correlation information into the deep neural network by developing a novel Hierarchical Semantic Embedding (HSE) framework.

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED IMAGE RECOGNITION REPRESENTATION LEARNING

Selective Sparse Sampling for Fine-Grained Image Recognition

ICCV 2019 Yao-DD/S3N

Fine-grained recognition poses the unique challenge of capturing subtle inter-class differences under considerable intra-class variances (e. g., beaks for bird species).

FINE-GRAINED IMAGE CLASSIFICATION FINE-GRAINED IMAGE RECOGNITION

Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

ECCV 2018 xcnkx/fine_grained_classification

Attention-based learning for fine-grained image recognition remains a challenging task, where most of the existing methods treat each object part in isolation, while neglecting the correlations among them.

FINE-GRAINED IMAGE RECOGNITION METRIC LEARNING

Pay attention to the activations: a modular attention mechanism for fine-grained image recognition

30 Jul 2019prlz77/attend-and-rectify

Attention has been typically implemented in neural networks by selecting the most informative regions of the image that improve classification.

FINE-GRAINED IMAGE RECOGNITION