Matches in SemOpenAlex for { <https://semopenalex.org/work/W2945895945> ?p ?o ?g. }
- W2945895945 abstract "Hand-drawn sketch recognition is a fundamental problem in computer vision, widely used in sketch-based image and video retrieval, editing, and reorganization. Previous methods often assume that a complete sketch is used as input; however, hand-drawn sketches in common application scenarios are often incomplete, which makes sketch recognition a challenging problem. In this paper, we propose SketchGAN, a new generative adversarial network (GAN) based approach that jointly completes and recognizes a sketch, boosting the performance of both tasks. Specifically, we use a cascade Encode-Decoder network to complete the input sketch in an iterative manner, and employ an auxiliary sketch recognition task to recognize the completed sketch. Experiments on the Sketchy database benchmark demonstrate that our joint learning approach achieves competitive sketch completion and recognition performance compared with the state-of-the-art methods. Further experiments using several sketch-based applications also validate the performance of our method." @default.
- W2945895945 created "2019-05-29" @default.
- W2945895945 creator A5002273236 @default.
- W2945895945 creator A5008076279 @default.
- W2945895945 creator A5013118329 @default.
- W2945895945 creator A5067850699 @default.
- W2945895945 creator A5084660341 @default.
- W2945895945 creator A5085025467 @default.
- W2945895945 date "2019-06-01" @default.
- W2945895945 modified "2023-09-27" @default.
- W2945895945 title "SketchGAN: Joint Sketch Completion and Recognition With Generative Adversarial Network" @default.
- W2945895945 cites W134498629 @default.
- W2945895945 cites W1972420097 @default.
- W2945895945 cites W1975049209 @default.
- W2945895945 cites W1976664910 @default.
- W2945895945 cites W1986413821 @default.
- W2945895945 cites W2055231701 @default.
- W2945895945 cites W2100415658 @default.
- W2945895945 cites W2110158442 @default.
- W2945895945 cites W2153404544 @default.
- W2945895945 cites W2160411867 @default.
- W2945895945 cites W2295934715 @default.
- W2945895945 cites W2346755835 @default.
- W2945895945 cites W2466618734 @default.
- W2945895945 cites W2471581439 @default.
- W2945895945 cites W2493181180 @default.
- W2945895945 cites W2515723519 @default.
- W2945895945 cites W2557414982 @default.
- W2945895945 cites W2587706859 @default.
- W2945895945 cites W2603445054 @default.
- W2945895945 cites W2765837117 @default.
- W2945895945 cites W2767170755 @default.
- W2945895945 cites W2788865504 @default.
- W2945895945 cites W2798372101 @default.
- W2945895945 cites W2798685991 @default.
- W2945895945 cites W2798813225 @default.
- W2945895945 cites W2799062770 @default.
- W2945895945 cites W2962927829 @default.
- W2945895945 cites W2963073614 @default.
- W2945895945 cites W2963420272 @default.
- W2945895945 cites W2963426391 @default.
- W2945895945 cites W2963561004 @default.
- W2945895945 cites W2963767194 @default.
- W2945895945 cites W2963914894 @default.
- W2945895945 cites W2964024144 @default.
- W2945895945 cites W2964203072 @default.
- W2945895945 cites W2964266708 @default.
- W2945895945 cites W2964337551 @default.
- W2945895945 cites W3043547428 @default.
- W2945895945 cites W3106468843 @default.
- W2945895945 cites W3144890709 @default.
- W2945895945 doi "https://doi.org/10.1109/cvpr.2019.00598" @default.
- W2945895945 hasPublicationYear "2019" @default.
- W2945895945 type Work @default.
- W2945895945 sameAs 2945895945 @default.
- W2945895945 citedByCount "44" @default.
- W2945895945 countsByYear W29458959452019 @default.
- W2945895945 countsByYear W29458959452020 @default.
- W2945895945 countsByYear W29458959452021 @default.
- W2945895945 countsByYear W29458959452022 @default.
- W2945895945 countsByYear W29458959452023 @default.
- W2945895945 crossrefType "proceedings-article" @default.
- W2945895945 hasAuthorship W2945895945A5002273236 @default.
- W2945895945 hasAuthorship W2945895945A5008076279 @default.
- W2945895945 hasAuthorship W2945895945A5013118329 @default.
- W2945895945 hasAuthorship W2945895945A5067850699 @default.
- W2945895945 hasAuthorship W2945895945A5084660341 @default.
- W2945895945 hasAuthorship W2945895945A5085025467 @default.
- W2945895945 hasBestOaLocation W29458959452 @default.
- W2945895945 hasConcept C104317684 @default.
- W2945895945 hasConcept C11413529 @default.
- W2945895945 hasConcept C119857082 @default.
- W2945895945 hasConcept C13280743 @default.
- W2945895945 hasConcept C132900626 @default.
- W2945895945 hasConcept C153180895 @default.
- W2945895945 hasConcept C154945302 @default.
- W2945895945 hasConcept C159437735 @default.
- W2945895945 hasConcept C185592680 @default.
- W2945895945 hasConcept C185798385 @default.
- W2945895945 hasConcept C205649164 @default.
- W2945895945 hasConcept C207347870 @default.
- W2945895945 hasConcept C2779231336 @default.
- W2945895945 hasConcept C37736160 @default.
- W2945895945 hasConcept C39890363 @default.
- W2945895945 hasConcept C41008148 @default.
- W2945895945 hasConcept C46686674 @default.
- W2945895945 hasConcept C55493867 @default.
- W2945895945 hasConcept C66746571 @default.
- W2945895945 hasConceptScore W2945895945C104317684 @default.
- W2945895945 hasConceptScore W2945895945C11413529 @default.
- W2945895945 hasConceptScore W2945895945C119857082 @default.
- W2945895945 hasConceptScore W2945895945C13280743 @default.
- W2945895945 hasConceptScore W2945895945C132900626 @default.
- W2945895945 hasConceptScore W2945895945C153180895 @default.
- W2945895945 hasConceptScore W2945895945C154945302 @default.
- W2945895945 hasConceptScore W2945895945C159437735 @default.
- W2945895945 hasConceptScore W2945895945C185592680 @default.
- W2945895945 hasConceptScore W2945895945C185798385 @default.
- W2945895945 hasConceptScore W2945895945C205649164 @default.
- W2945895945 hasConceptScore W2945895945C207347870 @default.