(Arxiv'19) Learning Video Representations using Contrastive Bidirectional Transformer (Arxiv'19) Learning Spatiotemporal Features via Video and Text Pair Discrimination (CVPR'20 Oral) End-to-End Learning of Visual Representations from Uncurated Instructional Videos (简称MIL-NCE) (ICCV'19 Oral) VATEX:...
machine-learning deep-learning time-series language-model time-series-analysis time-series-forecast time-series-forecasting multimodal-deep-learning cross-modality multimodal-time-series cross-modal-learning prompt-tuning large-language-models Updated Nov 3, 2024 Python whwu95 / Cap4Video Star 248...
第一篇将侧重 "multi-modal" 和 "application", 介绍相关概念与研究背景;第二、三篇会侧重"algorithm" 介绍这个方向研究的技术路线,其中第二篇介绍基于 GAN 的追求公共子空间的cross-modal检索;第三篇则从modal抽象成更一般的domain,并且将多域扩展到单域,总结分析单/多域匹配问题,主要介绍基于contrastivelearning ...
Cross-Modal LearningSynonymsSynonymsMultimodal learningDefinitionDefinitionCross-modal learning refers to any kind of learning that involves information obtained from more than one modality. In the literature the term modoi:10.1007/978-1-4419-1428-6_239Danijel Skocaj...
1.Learning Cross-Modal Deep Representations for Robust Pedestrian Detection. In CVPR, 2017. 2.S. Gupta, J. Hoffman, and J. Malik. Cross modal distillationfor supervision transfer. InCVPR, 2016. 3. J. Hoffman, S. Gupta, and T. Darrell. Learning with sideinformation through modality hallucina...
论文阅读:CMCLRec: Cross-modal Contrastive Learning for User Cold-start Sequential Recommendation 摘要 顺序推荐模型通过对历史用户 - 项目交互的分析为项目生成嵌入向量,并利用所获得的嵌入向量来预测用户偏好。尽管这些模型在揭示用户的个性化偏好方面很有效,但它们严重依赖用户 - 项目交互。然而,由于缺乏交互信息,新...
In this paper, we propose a semi-supervised algorithm for cross modal learning. Our algorithm can make full use of both a small number of labeled and an abundant unlabeled data to establish connections between modalities via a shared semantic space discovering. On the other hand, our algorithm ...
This leads to an important research direction: cross-modal learning. In this paper, we introduce a method based on the content of audio and video data modalities implemented with a novel two-branch neural network is to learn the joint embeddings from a shared subspace for computing the ...
Learning Hierarchical Cross-Modal Association for Co-Speech Gesture Generation Xian Liu1, Qianyi Wu2, Hang Zhou1, Yinghao Xu1, Rui Qian1, Xinyi Lin3, Xiaowei Zhou3, Wayne Wu4, Bo Dai5, Bolei Zhou1 1The Chinese University of Hong Kong 2Monash Univers...
In this paper, we propose novel Disentangled Adversarial examples for Cross-Modal learning, dubbed DACM. Specifically, we first divide cross-modal data into two aspects, namely modality-related component and modality-unrelated counterpart, and then learn to improve the reliability of network using ...