在ActivityNet 数据集上的实验结果 在LSMDC 数据集上的实验结果 对于是否在 HowTo100M 数据集上预训练的消融实验 不同标题特征提取模型的消融实验结果 更多消融实验 使用各种模态的消融实验结果 论文信息 Multi-modal Transformer for Video Retrieval arxiv.org/pdf/2007.1063 发布于 2021-11-12 16:46 ...
Transformer key idea主要是来源于:Attention is all you need一文;本文每个层之间的 Transformer takes as inputa sequenceconsisting ofdiscrete tokens, each represented by a feature vector. The feature vector is supplemented bya positional encodingto incorporatepositional inductive biases 总的来说就是 emmm ...
Our method relies on a multi-modal transformer model that encodes past observations and produces predictions at different anticipation times, employing a learned mask technique to filter out redundancy in the observed frames. Instead of relying solely on visual cues extracted from images or videos, ...
Transformerkey idea主要是来源于:Attention is all you need 一文;本文每个层之间的 Transformer takes as input a sequence consisting of discrete tokens, each represented by a feature vector. The feature vector is supplemented by a positional encoding to incorporate positional inductive biases...
总之，本文通过引入count-guided multi-modal fusion和modal-guided counting enhancement概念，结合Transformer架构和多尺度token transformer结构，有效解决了RGB-T多模态人群计数问题，并在多个实验指标上表现出色。这一工作为多模态人群计数任务提供了一种新的解决方案。
Pan等人提出了一种使用基于transformer的系统检索最相关表格并定位正确单元格的方法。此外,为了改进视频QA,Hu等人从存储在内存中的知识图谱编码中检索。 一般文本生成:外部知识检索可以提高一般文本生成的事实性。Liu等人提出了一种内存增强方法,以依据知识图谱条件化自回归语言模型。在推理过程中,Tan等人通过密集检索选择...
Our proposed Multi-Modal Transformer (MMT) aggregates sequences of multi-modal features (e.g. appearance, motion, audio, OCR, etc.) from a video. It then embeds the aggregated multi-modal feature to a shared space with text for retrieval. It achieves state-of-the-art performance on MSRVT...
Summary Sequence-based deep learning models have emerged as powerful tools for deciphering the cis -regulatory grammar of the human genome but cannot generalize to unobserved cellular contexts. Here, we present EpiBERT, a multi-modal transformer that learns generalizable representations of genomic sequenc...
1) Cross Transformer Encoder 我们的cross transformer旨在有效地融合这两种模式。 2) Cross Attention Module Our cross attention module is an improved multi-head attention module which absorbs features from the auxiliary modality that contribute to the target modality.具体来说,为了更有效地融合不同的模式,...
在transformer的输入信息中,除了每个stage输出的token,还需要融合位置编码,显然尺寸和cat之后的特征相同,初次之外还融合了当前自车的速度信息,即将速度标量线性映射成长度为C的特征向量后叠加到输入上。 为了降低计算规模,从feature map中提取token时可以采用平均池化的方式减少token的数量,然后再在与分支叠加时使用上采样...