Detecting Visual Relationships Using Box Attention

07/05/2018
by   Alexander Kolesnikov, et al.
0

In this paper we propose a new model for detecting visual relationships. Our main technical novelty is a Box Attention mechanism that allows modelling pairwise interactions between objects in visual scenes using standard object detection pipelines. The resulting model is conceptually clean, expressive and relies on well-justified training and prediction procedures. Moreover, unlike previously proposed approaches, our model does not introduce any additional complex components or hyperparameters on top of those already required by the underlying detection model. We conduct an experimental evaluation on two challenging datasets, V-COCO and Visual Relationships, demonstrating strong quantitative and qualitative results.

READ FULL TEXT

page 3

page 4

page 6

research
02/06/2017

Attentional Network for Visual Object Detection

We propose augmenting deep neural networks with an attention mechanism f...
research
03/08/2021

Relationship-based Neural Baby Talk

Understanding interactions between objects in an image is an important e...
research
09/10/2020

RVL-BERT: Visual Relationship Detection with Visual-Linguistic Knowledge from Pre-trained Representations

Visual relationship detection aims to reason over relationships among sa...
research
12/20/2016

Action-Driven Object Detection with Top-Down Visual Attentions

A dominant paradigm for deep learning based object detection relies on a...
research
10/05/2022

AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation

Temporal action proposal generation (TAPG) is a challenging task, which ...
research
12/10/2021

IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes

Building embodied intelligent agents that can interact with 3D indoor en...
research
04/04/2021

Learning Image Aesthetic Assessment from Object-level Visual Components

As it is said by Van Gogh, great things are done by a series of small th...

Please sign up or login with your details

Forgot password? Click here to reset