- Image|Text Embedding Learning via Visual and Textual Semantic ...🔍
- Improve Visual Semantic Embeddings via Regularization for Image ...🔍
- Learning Asymmetric Visual Semantic Embedding for Image|Text ...🔍
- Improving visual|semantic embeddings by learning semantically ...🔍
- Multi|Task Visual Semantic Embedding Network for Image|Text ...🔍
- Emergent Visual|Semantic Hierarchies in Image|Text Representations🔍
- Methods Summary of Conventional Image|Text Matching🔍
- Consensus|Aware Visual|Semantic Embedding for Image|Text ...🔍
Image|Text Embedding Learning via Visual and Textual Semantic ...
Image-Text Embedding Learning via Visual and Textual Semantic ...
We introduce an intuitive and interpretable model to learn a common embedding space for alignments between images and text descriptions.
Image-Text Embedding Learning via Visual and Textual Semantic ...
As a bridge between language and vision domains, cross-modal retrieval between images and texts is a hot research topic in recent years.
Image-Text Embedding Learning via Visual and Textual Semantic ...
This work introduces an intuitive and interpretable model to learn a common embedding space for alignments between images and text descriptions and shows ...
Image-Text Embedding Learning via Visual and Textual Semantic ...
Image-Text Embedding Learning via Visual and Textual Semantic Reasoning. ... As a bridge between language and vision domains, cross-modal retrieval between images ...
Image-Text Embedding Learning via Visual and Textual Semantic ...
(DOI: 10.1109/tpami.2022.3148470) As a bridge between language and vision domains, cross-modal retrieval between images and texts is a hot ...
Improve Visual Semantic Embeddings via Regularization for Image ...
Cross-modal Graph Matching Network for Image-text Retrieval. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) ...
Learning Asymmetric Visual Semantic Embedding for Image-Text ...
Abstract: Learning visual semantic similarity is the key challenge to bridge the correspondences between images and texts. However, there are many inherent ...
Improving visual-semantic embeddings by learning semantically ...
[9] presented a margin-adaptive triplet loss for the task of cross-modal information retrieval that uses a hashing-based method which embeds the image and text ...
Multi-Task Visual Semantic Embedding Network for Image-Text ...
Besides, we present an intra- and inter-modality interaction scheme to learn discriminative visual and textual feature representations by ...
Emergent Visual-Semantic Hierarchies in Image-Text Representations
Images may be described by multiple valid texts of varying granularity levels, forming a hierarchy which may be learned or exploited in various ...
Methods Summary of Conventional Image-Text Matching - GitHub
... Text-Image Retrieval. Siyu Ren, Kenny Q. Zhu. [paper] [code]. (TPAMI2022_VSRN++) Image-Text Embedding Learning via Visual and Textual Semantic Reasoning.
DeViSE: A Deep Visual-Semantic Embedding Model
vector representation of the image label text as learned by the language model. ... Zero-shot learning by convex combination of semantic embeddings. arXiv ...
Consensus-Aware Visual-Semantic Embedding for Image-Text ...
[30] adopted. CNN and Recurrent Neural Network (RNN) to represent images and texts, fol- lowed by employing bidirectional triplet ranking loss to learn a joint ...
Learning Semantic Relationship Among Instances for Image-Text ...
Since the heterogeneity between visual and textual se- mantics, directly using global embeddings is insufficient to identify the inter-modal connection relation ...
Multi-view visual semantic embedding for cross-modal image-text ...
We propose a unified loss that incorporates the triplet loss and contrastive loss into a unified form, and extends it to multi-view learning. •.
Uncovering the Text Embedding in Text-to-Image Diffusion Models
For instance, the approach of textual inversion [5] involves learning to transform image concepts into new text embeddings using a frozen text-to-image model.
[PDF] Improving visual-semantic embeddings by learning ...
Semantic Scholar extracted view of "Improving visual-semantic embeddings by learning semantically ... Image-Text Embedding Learning via Visual and Textual ...
Trust-consistent Visual Semantic Embedding for Image-Text Matching
learning cross-modal embeddings to bridge the discrepancy across visual and textual spaces. In recent years, VSE has achieved great success ...
Semantic Embedding Uncertainty Learning for Image and Text ...
... embedding, which mines the intrinsic characteristics of visual and textual for discriminative representation. However, cross-modal ambiguity of image and text ...
Aligning Visual Regions and Textual Concepts for Semantic ...
Existing downstream systems achieve that by using both kinds of image representations in the decoding process, mostly ignoring the innate alignment between the ...