FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2889658408> ?p ?o ?g. }

• W2889658408 endingPage "73" @default.
• W2889658408 startingPage "56" @default.
• W2889658408 abstract "Video object segmentation is challenging yet important in a wide variety of applications for video analysis. Recent works formulate video object segmentation as a prediction task using deep nets to achieve appealing state-of-the-art performance. Due to the formulation as a prediction task, most of these methods require fine-tuning during test time, such that the deep nets memorize the appearance of the objects of interest in the given video. However, fine-tuning is time-consuming and computationally expensive, hence the algorithms are far from real time. To address this issue, we develop a novel matching based algorithm for video object segmentation. In contrast to memorization based classification techniques, the proposed approach learns to match extracted features to a provided template without memorizing the appearance of the objects. We validate the effectiveness and the robustness of the proposed method on the challenging DAVIS-16, DAVIS-17, Youtube-Objects and JumpCut datasets. Extensive results show that our method achieves comparable performance without fine-tuning and is much more favorable in terms of computational time." @default.
• W2889658408 created "2018-09-27" @default.
• W2889658408 creator A5006947125 @default.
• W2889658408 creator A5049638480 @default.
• W2889658408 creator A5073412478 @default.
• W2889658408 date "2018-01-01" @default.
• W2889658408 modified "2023-09-30" @default.
• W2889658408 title "VideoMatch: Matching Based Video Object Segmentation" @default.
• W2889658408 cites W1560354729 @default.
• W2889658408 cites W1762798876 @default.
• W2889658408 cites W1973054923 @default.
• W2889658408 cites W1989348325 @default.
• W2889658408 cites W1995903777 @default.
• W2889658408 cites W2009874829 @default.
• W2889658408 cites W2016163842 @default.
• W2889658408 cites W2030346542 @default.
• W2889658408 cites W2034740917 @default.
• W2889658408 cites W2037227137 @default.
• W2889658408 cites W2068994826 @default.
• W2889658408 cites W2076756823 @default.
• W2889658408 cites W2088780408 @default.
• W2889658408 cites W2102840968 @default.
• W2889658408 cites W2113708607 @default.
• W2889658408 cites W2138682569 @default.
• W2889658408 cites W2144794286 @default.
• W2889658408 cites W2151103935 @default.
• W2889658408 cites W2156547441 @default.
• W2889658408 cites W2158827467 @default.
• W2889658408 cites W2177274842 @default.
• W2889658408 cites W2194775991 @default.
• W2889658408 cites W2200599981 @default.
• W2889658408 cites W2212077366 @default.
• W2889658408 cites W2322739735 @default.
• W2889658408 cites W2412782625 @default.
• W2889658408 cites W2460260369 @default.
• W2889658408 cites W2463175074 @default.
• W2889658408 cites W2467181293 @default.
• W2889658408 cites W2470139095 @default.
• W2889658408 cites W2470394683 @default.
• W2889658408 cites W2562457735 @default.
• W2889658408 cites W2564998703 @default.
• W2889658408 cites W2566030665 @default.
• W2889658408 cites W2604233003 @default.
• W2889658408 cites W2610147486 @default.
• W2889658408 cites W2750515003 @default.
• W2889658408 cites W2777921528 @default.
• W2889658408 cites W2799157347 @default.
• W2889658408 cites W2799239273 @default.
• W2889658408 cites W2890853604 @default.
• W2889658408 cites W2962825871 @default.
• W2889658408 cites W2963131444 @default.
• W2889658408 cites W2963253279 @default.
• W2889658408 cites W2963548592 @default.
• W2889658408 cites W2963732700 @default.
• W2889658408 cites W2963983744 @default.
• W2889658408 cites W2964157492 @default.
• W2889658408 cites W4211189038 @default.
• W2889658408 cites W589665618 @default.
• W2889658408 cites W764651262 @default.
• W2889658408 doi "https://doi.org/10.1007/978-3-030-01237-3_4" @default.
• W2889658408 hasPublicationYear "2018" @default.
• W2889658408 type Work @default.
• W2889658408 sameAs 2889658408 @default.
• W2889658408 citedByCount "166" @default.
• W2889658408 countsByYear W28896584082018 @default.
• W2889658408 countsByYear W28896584082019 @default.
• W2889658408 countsByYear W28896584082020 @default.
• W2889658408 countsByYear W28896584082021 @default.
• W2889658408 countsByYear W28896584082022 @default.
• W2889658408 countsByYear W28896584082023 @default.
• W2889658408 crossrefType "book-chapter" @default.
• W2889658408 hasAuthorship W2889658408A5006947125 @default.
• W2889658408 hasAuthorship W2889658408A5049638480 @default.
• W2889658408 hasAuthorship W2889658408A5073412478 @default.
• W2889658408 hasBestOaLocation W28896584082 @default.
• W2889658408 hasConcept C105795698 @default.
• W2889658408 hasConcept C153180895 @default.
• W2889658408 hasConcept C154945302 @default.
• W2889658408 hasConcept C165064840 @default.
• W2889658408 hasConcept C2781238097 @default.
• W2889658408 hasConcept C31972630 @default.
• W2889658408 hasConcept C33923547 @default.
• W2889658408 hasConcept C41008148 @default.
• W2889658408 hasConcept C89600930 @default.
• W2889658408 hasConceptScore W2889658408C105795698 @default.
• W2889658408 hasConceptScore W2889658408C153180895 @default.
• W2889658408 hasConceptScore W2889658408C154945302 @default.
• W2889658408 hasConceptScore W2889658408C165064840 @default.
• W2889658408 hasConceptScore W2889658408C2781238097 @default.
• W2889658408 hasConceptScore W2889658408C31972630 @default.
• W2889658408 hasConceptScore W2889658408C33923547 @default.
• W2889658408 hasConceptScore W2889658408C41008148 @default.
• W2889658408 hasConceptScore W2889658408C89600930 @default.
• W2889658408 hasLocation W28896584081 @default.
• W2889658408 hasLocation W28896584082 @default.
• W2889658408 hasOpenAccess W2889658408 @default.
• W2889658408 hasPrimaryLocation W28896584081 @default.
• W2889658408 hasRelatedWork W1669643531 @default.

• next