https://github.com/LCS2-IIITD/MSH-COMICS
공식 코드Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations
Papers with Code 아카이브
Multi-modal Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YuanGongND/uavm
공식 코드https://github.com/artelab/Multi-modal-classification
공식 코드Image and Encoded Text Fusion for Multi-Modal Classification
https://github.com/bezirganyan/DBF_uncertainty
공식 코드Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
https://github.com/brandonhanx/fame-vil
공식 코드FAME-ViL: Multi-Tasking Vision-Language Model for Heterogeneous Fashion Tasks
https://github.com/emu1729/gist
공식 코드GIST: Generating Image-Specific Text for Fine-grained Object Classification
https://github.com/glami/glami-1m
공식 코드https://github.com/guoyang9/AdaVQA
공식 코드https://github.com/halaa901/qnlp-thesis
공식 코드https://github.com/hybridNLP/look_read_and_enrich
공식 코드Look, Read and Enrich. Learning from Scientific Figures and their Captions
https://github.com/qitianwu/difformer
공식 코드DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
https://github.com/reycn/multi-modal-scale
공식 코드Hateful Meme Detection through Context-Sensitive Prompting and Fine-Grained Labeling
https://github.com/vincent-zhq/unis-mmc
공식 코드UniS-MMC: Multimodal Classification via Unimodality-supervised Multimodal Contrastive Learning
https://github.com/yuangongnd/cav-mae
공식 코드https://github.com/zhjohnchan/ptunifier
공식 코드Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts
https://github.com/facebookresearch/R2Plus1D
What Makes Training Multi-Modal Classification Networks Hard?
https://github.com/facebookresearch/VMZ
What Makes Training Multi-Modal Classification Networks Hard?
https://github.com/guide2157/ChulaXrayClassifier
What Makes Training Multi-Modal Classification Networks Hard?
https://github.com/zhanghr2001/promptta
PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.