[图书][B] Synthetic data for deep learning

SI Nikolenko - 2021 - Springer
You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Structured domain randomization: Bridging the reality gap by context-aware synthetic data

A Prakash, S Boochoon, M Brophy… - … on Robotics and …, 2019 - ieeexplore.ieee.org
We present structured domain randomization (SDR), a variant of domain randomization
(DR) that takes into account the structure of the scene in order to add context to the …

Invariant information bottleneck for domain generalization

B Li, Y Shen, Y Wang, W Zhu, D Li, K Keutzer… - Proceedings of the …, 2022 - ojs.aaai.org
Invariant risk minimization (IRM) has recently emerged as a promising alternative for domain
generalization. Nevertheless, the loss function is difficult to optimize for nonlinear classifiers …

Akb-48: A real-world articulated object knowledge base

L Liu, W Xu, H Fu, S Qian, Q Yu… - Proceedings of the …, 2022 - openaccess.thecvf.com
Human life is populated with articulated objects. A comprehensive understanding of
articulated objects, namely appearance, structure, physics property, and semantics, will …

An annotation saved is an annotation earned: Using fully synthetic training for object detection

S Hinterstoisser, O Pauly, H Heibel… - Proceedings of the …, 2019 - openaccess.thecvf.com
Deep learning methods typically require vast amounts of training data to reach their full
potential. While some publicly available datasets exists, domain specific data always needs …

Synthetic Data for Object Detection with Neural Networks: State-of-the-Art Survey of Domain Randomisation Techniques

A Westerski, WT Fong - ACM Transactions on Multimedia Computing …, 2024 - dl.acm.org
Machine learning relies heavily on access to large and well-maintained datasets. In this
article, we focus on Computer Vision and object detection applications to survey past …

Text to image synthesis for improved image captioning

MZ Hossain, F Sohel, MF Shiratuddin, H Laga… - IEEE …, 2021 - ieeexplore.ieee.org
Generating textual descriptions of images has been an important topic in computer vision
and natural language processing. A number of techniques based on deep learning have …

Auto-generated wires dataset for semantic segmentation with domain-independence

R Zanella, A Caporali, K Tadaka… - … on computer, control …, 2021 - ieeexplore.ieee.org
In this work, we present a procedure to automatically generate an high-quality training
dataset of cable-like objects for semantic segmentation. The proposed method is explained …

Toward real-world category-level articulation pose estimation

L Liu, H Xue, W Xu, H Fu, C Lu - IEEE Transactions on Image …, 2022 - ieeexplore.ieee.org
Human life is populated with articulated objects. Current Category-level Articulation Pose
Estimation (CAPE) methods are studied under the single-instance setting with a fixed …

PODB: A learning-based polarimetric object detection benchmark for road scenes in adverse weather conditions

Z Zhu, X Li, J Zhai, H Hu - Information Fusion, 2024 - Elsevier
Due to its insensitivity to light intensity and the capability to capture multidimensional
information, polarimetric imaging technology has been proven to have advantages over …