Papers
22 papers found
Transformers at SemEval-2022 Task 5: A Feature Extraction based Approach for Misogynous Meme Detection
Shankar Mahadevan, Sean Benhur, Roshan Nayak et al.
PAIC at SemEval-2022 Task 5: Multi-Modal Misogynous Detection in MEMES with Multi-Task Learning And Multi-model Fusion
Jin Zhi, Zhou Mengyuan, Mengfei Yuan et al.
DD-TIG at SemEval-2022 Task 5: Investigating the Relationships Between Multimodal and Unimodal Information in Misogynous Memes Detection and Classification
Ziming Zhou, Han Zhao, Jingjing Dong et al.
UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes
Edgar Roman-Rangel, Jorge Fuentes-Pacheco, Jorge Hermosillo Valadez
RubCSG at SemEval-2022 Task 5: Ensemble learning for identifying misogynous MEMEs
Wentao Yu, Benedikt Boenninghoff, Jonas Röhrig et al.
MilaNLP at SemEval-2022 Task 5: Using Perceiver IO for Detecting Misogynous Memes with Text and Image Modalities
Giuseppe Attanasio, Debora Nozza, Federico Bianchi
IIITH at SemEval-2022 Task 5: A comparative study of deep learning models for identifying misogynous memes
Tathagata Raha, Sagar Joshi, Vasudeva Varma
Codec at SemEval-2022 Task 5: Multi-Modal Multi-Transformer Misogynous Meme Classification Framework
Ahmed Mahran, Carlo Alessandro Borella, Konstantinos Perifanos
MMVAE at SemEval-2022 Task 5: A Multi-modal Multi-task VAE on Misogynous Meme Detection
Yimeng Gu, Ignacio Castro, Gareth Tyson
TIB-VA at SemEval-2022 Task 5: A Multimodal Architecture for the Detection and Classification of Misogynous Memes
Sherzod Hakimov, Gullal Singh Cheema, Ralph Ewerth
Transformers at SemEval-2022 Task 5: A Feature Extraction based Approach for Misogynous Meme Detection
Shankar Mahadevan, Sean Benhur, Roshan Nayak et al.
PAIC at SemEval-2022 Task 5: Multi-Modal Misogynous Detection in MEMES with Multi-Task Learning And Multi-model Fusion
Jin Zhi, Zhou Mengyuan, Mengfei Yuan et al.
DD-TIG at SemEval-2022 Task 5: Investigating the Relationships Between Multimodal and Unimodal Information in Misogynous Memes Detection and Classification
Ziming Zhou, Han Zhao, Jingjing Dong et al.
UAEM-ITAM at SemEval-2022 Task 5: Vision-Language Approach to Recognize Misogynous Content in Memes
Edgar Roman-Rangel, Jorge Fuentes-Pacheco, Jorge Hermosillo Valadez
RubCSG at SemEval-2022 Task 5: Ensemble learning for identifying misogynous MEMEs
Wentao Yu, Benedikt Boenninghoff, Jonas Röhrig et al.
MilaNLP at SemEval-2022 Task 5: Using Perceiver IO for Detecting Misogynous Memes with Text and Image Modalities
Giuseppe Attanasio, Debora Nozza, Federico Bianchi
IIITH at SemEval-2022 Task 5: A comparative study of deep learning models for identifying misogynous memes
Tathagata Raha, Sagar Joshi, Vasudeva Varma
Codec at SemEval-2022 Task 5: Multi-Modal Multi-Transformer Misogynous Meme Classification Framework
Ahmed Mahran, Carlo Alessandro Borella, Konstantinos Perifanos
MMVAE at SemEval-2022 Task 5: A Multi-modal Multi-task VAE on Misogynous Meme Detection
Yimeng Gu, Ignacio Castro, Gareth Tyson
TIB-VA at SemEval-2022 Task 5: A Multimodal Architecture for the Detection and Classification of Misogynous Memes
Sherzod Hakimov, Gullal Singh Cheema, Ralph Ewerth