1) Large-scale weAk-supervised Image-Text (LAIT) dataset 2) Conceptual Captions dataset 3) SBU Captions Downstream Tasks: 1) Image-Text Retrieval 设备: 4 NVIDIA Tesla V100 GPU 2. 12-in-1 12-in-1: Multi-Task Vision and Language Representation Learning, CVPR 2020,[code] 之前的pre-training...
Digimon Dataset for MultiModal Machine Learning deep-learning image-generation clip text-image-retrieval Updated Jun 2, 2023 Python Improve this page Add a description, image, and links to the text-image-retrieval topic page so that developers can more easily learn about it. Curate this ...
下图是Image Encoders and Text Encoders示意图,左块是两种模态分别提取特征,中间是本文提出的GSE模块用来对视觉区域特征进行语义增强(每次选用sge/cge其中一个),右块是将局部特征合并成一整块特征。 评价 实验 Dataset: Flickr30K dataset : split into 29,000 training images, 1,000 validation images, and 1,...
To address these issues, we develop a novel modality interaction modeling network based upon the routing mechanism, which is the first unified and dynamic multimodal interaction framework towards image-text retrieval. In particular, we first design four types of cells as basic units to explore ...
Firstly, according to the analysis of Natural Language Processing technology, it acquires text keywords and semantic correlation of users' demands, and applies them to retrieve seed images from the image dataset by semantic relevance analysis. Then image extension retrieval based on SIFT feature are ...
The proposed MTH method is extensively tested on the Corel dataset with 15 000 natural images. The results demonstrate that it is much more efficient than representative image feature descriptors, such as the edge orientation auto-correlogram and the texton co-occurrence matrix. It has good ...
referring segmentation using post-hoc matching with referring texts. On the other hand, sending the text phrase as input to X-Decoder is essential to modulate our model to specifically decode the targets. VL Batch Size & Dataset The default batch size of VL task is 1024, here we explore the...
by the plurality of digital image searches 306 Generate a training dataset based on the plurality of text queries and the plurality of digital images 308 Train a model using machine learning based on a loss function using the training dataset 310 Generate a subsequent search result using the ...
Inspired by recently emerging interests on personalized image search in information retrieval research, the proposed method can infer users' implicit search intent better and provide more engaging search results according to trends of Web user photos. Firstly, we collect a user historical dataset ...
We proposed a semantical alignment strategy Visual Semantic Loss(VSL) for image-text retrieval. And we verify the effectiveness on top of two models proposed in SGRAF. Introduction The framework of VSL: The experiments result: Dataset Method Image to Text Text to Image R@1 R@5 R@10 R@1 ...