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picture1_Bilinear Transformation Example 178261 | 8680 Learning Deep Bilinear Transformation For Fine Grained Image Representation


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File: Bilinear Transformation Example 178261 | 8680 Learning Deep Bilinear Transformation For Fine Grained Image Representation
Learning Deep Bilinear Transformation for Fine-grained Image Representation 1∗ 2 1 3 Heliang Zheng , Jianlong Fu , Zheng-Jun Zha , Jiebo Luo 1University of Science and Technology of China, Hefei, China 2Microsoft ...

icon picture PDF Filetype PDF | Posted on 29 Jan 2023 | 2 years ago

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...Learning deep bilinear transformation for fine grained image representation heliang zheng jianlong fu jun zha jiebo luo university of science and technology china hefei microsoft research beijing rochester ny zhenghl mail ustc edu cn jianf com zhazj jluo cs abstract feature has shown the state art performance in ne representations however computational cost to learn pairwise interactions between deepfeaturechannelsisprohibitivelyexpensive which restricts this powerful be used neural networks paper we propose a dbt block can deeply stacked convolutional uniformly divide input channels into several semantic groups as represented by calculating within each group heavily relieved output is further obtained aggregating intra features with residuals from entire found that proposed network achieves new recognition benchmarks including cub bird stanford car fgvc aircraft introduction aims distinguish subtle visual differences subcategory e g various species models predominant approaches are of...
								

							

						
	
												
				
					
					
					
			
					
				
				
		
	

	
		





	

	
				

						

						
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										Category:  Uncategorized / Uncategorized 
										
Posted on: 29 Jan 2023 | 2 years ago
										
										
Tag:
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																								8680,
																								learning,
																								deep,
																								bilinear,
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																								image,
																								representation,
											                                        
																				
Filetype: PDF
										
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												Wan learn