Learning Fine-grained Image Similarity with Deep Ranking

ثبت نشده
چکیده

001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 CVPR #709 CVPR #709 CVPR 2014 Submission #709. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Learning deep similarity models with focus ranking for fabric image retrieval

Fabric image retrieval is beneficial to many applications including clothing searching, online shopping and cloth modeling. Learning pairwise image similarity is of great importance to an image retrieval task. With the resurgence of Convolutional Neural Networks (CNNs), recent works have achieved significant progresses via deep representation learning with metric embedding, which drives similar...

متن کامل

Lexical Simplification with the Deep Structured Similarity Model

We explore the application of a Deep Structured Similarity Model (DSSM) to ranking in lexical simplification. Our results show that the DSSM can effectively capture fine-grained features to perform semantic matching when ranking substitution candidates, outperforming the stateof-the-art on two standard datasets used for the task.

متن کامل

Image similarity using Deep CNN and Curriculum Learning

Image similarity involves fetching similar looking images given a reference image. Our solution called SimNet, is a deep siamese network which is trained on pairs of positive and negative images using a novel online pair mining strategy inspired by Curriculum learning. We also created a multi-scale CNN, where the final image embedding is a joint representation of top as well as lower layer embe...

متن کامل

Query-adaptive Image Retrieval by Deep Weighted Hashing

The hashing methods have attracted much attention for large scale image retrieval. Some deep hashing methods have achieved promising results by taking advantage of the better representation power of deep networks recently. However, existing deep hashing methods treat all hash bits equally. On one hand, a large number of images share the same distance to a query image because of the discrete Ham...

متن کامل

Deep Multi-task Attribute-driven Ranking for Fine-grained Sketch-based Image Retrieval

With touch-screen devices becoming ever more ubiquitous, sketch holds great promise as an intuitive and efficient mode of input compared to classic alternatives. This has motivated a major revival of interest in vision-based analysis of sketches, notably in sketch-based image retrieval (SBIR). Superior to classic SBIR methods, finegrained SBIR (FG-SBIR) methods [1] are proposed to make fine-gra...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014