Salient object detection: A survey

A Borji, MM Cheng, Q Hou, H Jiang, J Li - Computational visual media, 2019 - Springer
Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

Visual relationship detection with language priors

C Lu, R Krishna, M Bernstein, L Fei-Fei - … 11–14, 2016, Proceedings, Part I …, 2016 - Springer
Visual relationships capture a wide variety of interactions between pairs of objects in images
(eg “man riding bicycle” and “man pushing bicycle”). Consequently, the set of possible …

Understanding and evaluating racial biases in image captioning

D Zhao, A Wang… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Image captioning is an important task for benchmarking visual reasoning and for enabling
accessibility for people with vision impairments. However, as in many machine learning …

Detecting visual relationships with deep relational networks

B Dai, Y Zhang, D Lin - … of the IEEE conference on computer …, 2017 - openaccess.thecvf.com
Relationships among objects play a crucial role in image understanding. Despite the great
success of deep learning techniques in recognizing individual objects, reasoning about the …

Cider: Consensus-based image description evaluation

R Vedantam, C Lawrence Zitnick… - Proceedings of the …, 2015 - openaccess.thecvf.com
Automatically describing an image with a sentence is a long-standing challenge in computer
vision and natural language processing. Due to recent progress in object detection, attribute …

Factorizable net: an efficient subgraph-based framework for scene graph generation

Y Li, W Ouyang, B Zhou, J Shi… - Proceedings of the …, 2018 - openaccess.thecvf.com
Generating scene graph to describe all the relations inside an image gains increasing
interests these years. However, most of the previous methods use complicated structures …

REVISE: A tool for measuring and mitigating bias in visual datasets

A Wang, A Liu, R Zhang, A Kleiman, L Kim… - International Journal of …, 2022 - Springer
Abstract Machine learning models are known to perpetuate and even amplify the biases
present in the data. However, these data biases frequently do not become apparent until …

What makes a photograph memorable?

P Isola, J Xiao, D Parikh, A Torralba… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
When glancing at a magazine, or browsing the Internet, we are continuously exposed to
photographs. Despite this overflow of visual information, humans are extremely good at …

Seeing through the human reporting bias: Visual classifiers from noisy human-centric labels

I Misra, C Lawrence Zitnick, M Mitchell… - Proceedings of the …, 2016 - cv-foundation.org
When human annotators are given a choice about what to label in an image, they apply their
own subjective judgments on what to ignore and what to mention. We refer to these noisy" …

Best of both worlds: human-machine collaboration for object annotation

O Russakovsky, LJ Li, L Fei-Fei - Proceedings of the IEEE …, 2015 - cv-foundation.org
The long-standing goal of localizing every object in an image remains elusive. Manually
annotating objects is quite expensive despite crowd engineering innovations. Current state …