Matches in SemOpenAlex for { <https://semopenalex.org/work/W3092753574> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W3092753574 abstract "Facial micro-expressions (MEs) recognition has attracted much attention recently. However, because MEs are spontaneous, subtle and transient, recognizing MEs is a challenge task. In this paper, first, we use transfer learning to apply learning-based video motion magnification to magnify MEs and extract the shape information, aiming to solve the problem of the low muscle movement intensity of MEs. Then, we design a novel graph-temporal convolutional network (Graph-TCN) to extract the features of the local muscle movements of MEs. First, we define a graph structure based on the facial landmarks. Second, the Graph-TCN deals with the graph structure in dual channels with a TCN block. One channel is for node feature extraction, and the other one is for edge feature extraction. Last, the edges and nodes are fused for classification. The Graph-TCN can automatically train the graph representation to distinguish MEs while not using a hand-crafted graph representation. To the best of our knowledge, we are the first to use the learning-based video motion magnification method to extract the features of shape representations from the intermediate layer while magnifying MEs. Furthermore, we are also the first to use deep learning to automatically train the graph representation for MEs." @default.
- W3092753574 created "2020-10-22" @default.
- W3092753574 creator A5015527515 @default.
- W3092753574 creator A5048329422 @default.
- W3092753574 creator A5088172355 @default.
- W3092753574 creator A5090949378 @default.
- W3092753574 date "2020-10-12" @default.
- W3092753574 modified "2023-10-14" @default.
- W3092753574 title "A Novel Graph-TCN with a Graph Structured Representation for Micro-expression Recognition" @default.
- W3092753574 cites W1923404803 @default.
- W3092753574 cites W1998391547 @default.
- W3092753574 cites W2006426145 @default.
- W3092753574 cites W2059068649 @default.
- W3092753574 cites W2093033615 @default.
- W3092753574 cites W2101866605 @default.
- W3092753574 cites W2139916508 @default.
- W3092753574 cites W2194775991 @default.
- W3092753574 cites W2196663747 @default.
- W3092753574 cites W2237362194 @default.
- W3092753574 cites W2263218431 @default.
- W3092753574 cites W2426188534 @default.
- W3092753574 cites W2478411578 @default.
- W3092753574 cites W2526853616 @default.
- W3092753574 cites W2527254703 @default.
- W3092753574 cites W2623355927 @default.
- W3092753574 cites W2726381870 @default.
- W3092753574 cites W2787621021 @default.
- W3092753574 cites W2795270851 @default.
- W3092753574 cites W2805056734 @default.
- W3092753574 cites W2891138649 @default.
- W3092753574 cites W2957147054 @default.
- W3092753574 cites W2962875331 @default.
- W3092753574 cites W2964606879 @default.
- W3092753574 cites W2996566685 @default.
- W3092753574 cites W3100728255 @default.
- W3092753574 cites W3100951556 @default.
- W3092753574 cites W3103539074 @default.
- W3092753574 doi "https://doi.org/10.1145/3394171.3413714" @default.
- W3092753574 hasPublicationYear "2020" @default.
- W3092753574 type Work @default.
- W3092753574 sameAs 3092753574 @default.
- W3092753574 citedByCount "41" @default.
- W3092753574 countsByYear W30927535742020 @default.
- W3092753574 countsByYear W30927535742021 @default.
- W3092753574 countsByYear W30927535742022 @default.
- W3092753574 countsByYear W30927535742023 @default.
- W3092753574 crossrefType "proceedings-article" @default.
- W3092753574 hasAuthorship W3092753574A5015527515 @default.
- W3092753574 hasAuthorship W3092753574A5048329422 @default.
- W3092753574 hasAuthorship W3092753574A5088172355 @default.
- W3092753574 hasAuthorship W3092753574A5090949378 @default.
- W3092753574 hasConcept C132525143 @default.
- W3092753574 hasConcept C153180895 @default.
- W3092753574 hasConcept C154945302 @default.
- W3092753574 hasConcept C41008148 @default.
- W3092753574 hasConcept C52622490 @default.
- W3092753574 hasConcept C59404180 @default.
- W3092753574 hasConcept C80444323 @default.
- W3092753574 hasConceptScore W3092753574C132525143 @default.
- W3092753574 hasConceptScore W3092753574C153180895 @default.
- W3092753574 hasConceptScore W3092753574C154945302 @default.
- W3092753574 hasConceptScore W3092753574C41008148 @default.
- W3092753574 hasConceptScore W3092753574C52622490 @default.
- W3092753574 hasConceptScore W3092753574C59404180 @default.
- W3092753574 hasConceptScore W3092753574C80444323 @default.
- W3092753574 hasLocation W30927535741 @default.
- W3092753574 hasOpenAccess W3092753574 @default.
- W3092753574 hasPrimaryLocation W30927535741 @default.
- W3092753574 hasRelatedWork W1964120219 @default.
- W3092753574 hasRelatedWork W2000165426 @default.
- W3092753574 hasRelatedWork W2144059113 @default.
- W3092753574 hasRelatedWork W2146076056 @default.
- W3092753574 hasRelatedWork W2385132419 @default.
- W3092753574 hasRelatedWork W2546942002 @default.
- W3092753574 hasRelatedWork W2592385986 @default.
- W3092753574 hasRelatedWork W2772780115 @default.
- W3092753574 hasRelatedWork W2811390910 @default.
- W3092753574 hasRelatedWork W3003836766 @default.
- W3092753574 isParatext "false" @default.
- W3092753574 isRetracted "false" @default.
- W3092753574 magId "3092753574" @default.
- W3092753574 workType "article" @default.