A comprehensive survey of scene graphs: Generation and application
Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …
attributes, and relationships between objects in the scene. As computer vision technology …
Deep learning approaches on image captioning: A review
Image captioning is a research area of immense importance, aiming to generate natural
language descriptions for visual content in the form of still images. The advent of deep …
language descriptions for visual content in the form of still images. The advent of deep …
Reltr: Relation transformer for scene graph generation
Different objects in the same scene are more or less related to each other, but only a limited
number of these relationships are noteworthy. Inspired by Detection Transformer, which …
number of these relationships are noteworthy. Inspired by Detection Transformer, which …
Context-aware attention network for image-text retrieval
As a typical cross-modal problem, image-text bi-directional retrieval relies heavily on the
joint embedding learning and similarity measure for each image-text pair. It remains …
joint embedding learning and similarity measure for each image-text pair. It remains …
Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders
Despite the evolution of deep-learning-based visual-textual processing systems, precise
multi-modal matching remains a challenging task. In this work, we tackle the task of cross …
multi-modal matching remains a challenging task. In this work, we tackle the task of cross …
Cross-modal graph matching network for image-text retrieval
Image-text retrieval is a fundamental cross-modal task whose main idea is to learn image-
text matching. Generally, according to whether there exist interactions during the retrieval …
text matching. Generally, according to whether there exist interactions during the retrieval …
Lightningdot: Pre-training visual-semantic embeddings for real-time image-text retrieval
Multimodal pre-training has propelled great advancement in vision-and-language research.
These large-scale pre-trained models, although successful, fatefully suffer from slow …
These large-scale pre-trained models, although successful, fatefully suffer from slow …
Parts2words: Learning joint embedding of point clouds and texts by bidirectional matching between parts and words
Shape-Text matching is an important task of high-level shape understanding. Current
methods mainly represent a 3D shape as multiple 2D rendered views, which obviously can …
methods mainly represent a 3D shape as multiple 2D rendered views, which obviously can …
Transformer reasoning network for image-text matching and retrieval
Image-text matching is an interesting and fascinating task in modern AI research. Despite
the evolution of deep-learning-based image and text processing systems, multimodal …
the evolution of deep-learning-based image and text processing systems, multimodal …
Plug-and-play regulators for image-text matching
Exploiting fine-grained correspondence and visual-semantic alignments has shown great
potential in image-text matching. Generally, recent approaches first employ a cross-modal …
potential in image-text matching. Generally, recent approaches first employ a cross-modal …