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NUAA-QMUL at SemEval-2020 Task 8: Utilizing BERT and DenseNet for Internet Meme Emotion Analysis
XIAOYUGUO, JingMa, ArkaitzZubiaga....
Published date-11/05/2020
EmotionRecognition, ImageClassification
This paper describes our contribution to SemEval 2020 Task 8: Memotion Analysis. Our system learns multi-modal embeddings from text and images in order to classify Internet memes by sentiment. Our …
Transforming Facial Weight of Real Images by Editing Latent Space of StyleGAN
VNSRamaKrishnaPinnimty, MattZhao, PalakornAchananuparp....
Published date-11/05/2020
We present an invert-and-edit framework to automatically transform facial weight of an input face image to look thinner or heavier by leveraging semantic facial attributes encoded in the latent space …
Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers
ZhaoshuoLi, XingtongLiu, FrancisX.Creighton....
Published date-11/05/2020
DepthEstimation, StereoDepthEstimation
Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right image to infer depth. Rather than matching individual pixels, in this work, …
Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks
DavidPeer, SebastianStabinger, AntonioRodriguez-Sanchez....
Published date-11/05/2020
Designing neural network architectures is a challenging task and knowing which specific layers of a model must be adapted to improve the performance is almost a mystery. In this paper, …
Applying Machine Learning to Crowd-sourced Data from Earthquake Detective
OmkarRanadive, SuzanvanderLee, VivianTang....
Published date-11/05/2020
We present the Earthquake Detective dataset - A crowdsourced set of labels on potentially triggered (PT) earthquakes and tremors. These events are those which may have been triggered by large …
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition
MeikeNauta, AnnemarieJutte, JesperProvoost....
Published date-11/05/2020
Image recognition with prototypes is considered an interpretable alternative for black box deep learning models. Classification depends on the extent to which a test image "looks like" a prototype. However, …