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A survey on vision transformer
Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …
network mainly based on the self-attention mechanism. Thanks to its strong representation …
Ghostnet: More features from cheap operations
Deploying convolutional neural networks (CNNs) on embedded devices is difficult due to the
limited memory and computation resources. The redundancy in feature maps is an important …
limited memory and computation resources. The redundancy in feature maps is an important …
Towards unified text-based person retrieval: A large-scale multi-attribute and language search benchmark
In this paper, we introduce a large Multi-Attribute and Language Search dataset for text-
based person retrieval, called MALS, and explore the feasibility of performing pre-training on …
based person retrieval, called MALS, and explore the feasibility of performing pre-training on …
A survey on visual transformer
Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …
network mainly based on the self-attention mechanism. Thanks to its strong representation …
Attention, please! A survey of neural attention models in deep learning
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Abd-net: Attentive but diverse person re-identification
Attention mechanisms have been found effective for person re-identification (Re-ID).
However, the learned" attentive" features are often not naturally uncorrelated or" diverse" …
However, the learned" attentive" features are often not naturally uncorrelated or" diverse" …
Hierarchical deep click feature prediction for fine-grained image recognition
The click feature of an image, defined as the user click frequency vector of the image on a
predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained …
predefined word vocabulary, is known to effectively reduce the semantic gap for fine-grained …
GhostNets on heterogeneous devices via cheap operations
Deploying convolutional neural networks (CNNs) on mobile devices is difficult due to the
limited memory and computation resources. We aim to design efficient neural networks for …
limited memory and computation resources. We aim to design efficient neural networks for …
Beyond human parts: Dual part-aligned representations for person re-identification
Person re-identification is a challenging task due to various complex factors. Recent studies
have attempted to integrate human parsing results or externally defined attributes to help …
have attempted to integrate human parsing results or externally defined attributes to help …
Greedynas: Towards fast one-shot nas with greedy supernet
Training a supernet matters for one-shot neural architecture search (NAS) methods since it
serves as a basic performance estimator for different architectures (paths). Current methods …
serves as a basic performance estimator for different architectures (paths). Current methods …