论文链接:Cross-Modality Fusion Transformer for Multispectral Object Detection 论文代码:https://github.com/DocF/multispectral-object-detection Motivation 以往CNNs的工作,没有对长距离和全局的信息进行建模。本文提出一种Cross-Modality Fusion Transformer(CFT)模块,通过Transformer的能力充分挖掘全局上下文信息。Attentio...
Cross-Modality Transformer for Visible-Infrared Person Re-Identification USTC 张天柱组的工作 Visible-Infrared Person Re-Identification的任务:对于一个给定的行人的RGB图,要检索出同一人的IR图,反之亦然。 该任务的挑战:(1)两种模态间存在较大的跨模态差异;(2)同一模态中,同一行人的RGB图或者IR图也会有巨大...
The existing methods mainly face the problem of insufficient perception of modality information, and can not learn good discriminative modality-invariant embeddings for identities, which limits their performance. To solve these problems, we propose a new cross-modality transformer-based method (CMTR) ...
Transformer:多头注意力机制 加上 位置编码,就是 transformer 模型的核心。 Single-Modality Encoder: 在进行模态交互之前,作者首先对单个模态进行 self-attention 处理。也就是图 1 中的如下这个模块: Cross-Modality Encoder: 每一个 cross-modality layer 都包含 两个self-attention sub-layers, 一个bi-directional...
The first block combines the French and English text modalities, and the resulting tokens are combined with the audio modality. The final class token is passed to the MLP classification head to make the final predictions Full size image In the first transformer block, we introduce the learnable ...
temporal attentive cross-modality transformer model for long-term traffic predictions, namely xMTrans, with capability of exploring the temporal correlations between the data of two modalities: one target modality (for prediction, e.g., traffic congestion) and one support modality (e.g., people ...
In training process, we randomly use only a single modality for train- ing, such as camera or LiDAR, with the ratio of η1 and η2. This strategy ensures that the model are fully trained with both single modal and multi-modal. Then the model can be teste...
Addressing the issue of inaccurate multimodal representation for MSA, MMMT effectively combines mutual information maximization with crossmodal Transformer to convey more modality-invariant information to multimodal representation, fully exploring modal commonalities. Notably, it utilizes multi-modal labels for ...
[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection - Woogie-Boogie/CMT
[ICCV 2023] Cross Modal Transformer: Towards Fast and Robust 3D Object Detection CMT_nuScenes_testset.mp4 Performance comparison and Robustness under sensor failure. All statistics are measured on a single Tesla A100 GPU using the best model of official repositories. All models use spconv Voxeliza...