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...
Cross-Modality Fusion Transformer for Multispectral Object Detection
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...
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 test...
Paper tables with annotated results for CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification
In order to better combine the two modalities, we propose a novel Cross-Modal Transformer for human action recognition鈥擟MF-Transformer, which effectively fuses two different modalities. In spatio-temporal modality, video frames are used as inputs and directional attention is used in the ...
To solve these problems, we propose a cross-modality transformer-based method (CMTR) for the visible-infrared person re-identification task, which can explicitly mine the information of each modality and generate better discriminative features based on it. Specifically, to capture modalities' ...
The cross-modal transformer con- catenates two pathways of motion and music encodings, both of which are obtained through a sequence of layers in- cluding 2D convolution (purple blocks in Figure 2), 2D-1D reshaping (red), residual convolution (green) and modality- specific transformers (...
CMOT: A cross-modality transformer for RGB-D fusion in person re-identification with online learning capabilities 2024, Knowledge-Based Systems Citation Excerpt : Additional methods, such as SM-SGE (12.8%), Distillation (41.3%), SimMC (12.3%), and Hi-MPC (17.4%), manifest significantly lower...
ConfigModalitymAPNDSScheduleInference FPS vov_1600x640C42.9%48.1%20e8.4 voxel0075L65.3%70.1%15e+5e18.1 voxel0075_vov_1600x640C+L72.0%74.1%15e+5e6.0 Citation If you find CMT helpful in your research, please consider citing: @article{yan2023cross,title={Cross Modal Transformer via Coordinates Enc...