转为二值: 5.2 Hierarchical Discriminative Learning 同时引入K个分层的多重分类任务: 特别地,我们将第i个实例的K个分层图像哈希表示输入给K个多层感知器,如下所示: 最后,采用负对数似然损失对K个分层判别分类: 式中ρk为第k层的置信度,log(·)为元素对数函数。 5.3 Regularized Cross-modal Hashing 在上面,我...
此外,由于这种损失,来自不同配方组件的嵌入彼此对齐,这允许我们在测试时恢复(或产生幻觉)它们。 我们的方法使用简单但功能强大的模型组件对食谱和图像进行编码,并通过使用配对和非配对数据进行优化,这得益于新的自我监督食谱损失。我们的方法在Recipe1M(社区中最流行的数据集之一)上实现了最先进的结果。我们进行消融研究...
In this paper, we pay attention to the specific case in which images are both labeled with a category and annotated with free text, and develop a supervised multi-modal hierarchical semantic model (smHSM), where we incorporate image classification into the joint modeling of visual and textual ...
Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model. [pdf] Chengjiang Li, Yixin Cao, Lei Hou, Jiaxin Shi, Juanzi Li, Tat-Seng Chua. EMNLP 2019 A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching. [pdf] Jihun Choi, Taeuk ...
Fine-grained Multi-Modal Self-Supervised Learning. BMVC 2021[paper] Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences. CVPR Workshops 2020[paper] Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization. ...
(Wang et al.2009), supervised Hierarchical Dirichlet Processes Zhang et al. (2013), Storkey and Dai (2014), and maximum margin supervised topic model,MedLDA(Zhu et al.2012a). These models have shown to improve document classification performance (Zhu et al.2013a; Jiang et al.2012; Zhu ...
(DASFAA'2023) ML-KGCL: Multi-level Knowledge Graph Contrastive Learning for Recommendation [paper] (ICME'2023) Hierarchical and Contrastive Representation Learning for Knowledge-Aware Recommendation [paper] (WSDM'2023) Knowledge-Adaptive Contrastive Learning for Recommendation [paper]Generative...
SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation.[pdf] Ting Liu, Miaomiao Zhang, Mehran Javanmardi, Nisha Ramesh, Tolga Tasdizen.ECCV 2015 2013 Semi-supervised Learning for Large Scale Image Cosegmentation.[pdf] ...
Semi-Supervised Semantic Segmentation With Cross Pseudo Supervision.[pdf][code] Xiaokang Chen, Yuhui Yuan, Gang Zeng, Jingdong Wang.CVPR 2021. Semi-supervised Semantic Segmentation with Directional Context-aware Consistency.[pdf][code] Xin Lai, Zhuotao Tian, Li Jiang, Shu Liu, Hengshuang Zhao, ...
cross-modal understanding, and predicting the most suitable answer. The two major factors that have the potential to enhance the effectiveness of VQA are the model architecture and the data. VQA is a data-intensive task that requires substantial amounts of labelled training data. A good dataset ...