[HTML][HTML] Data augmentation: A comprehensive survey of modern approaches

A Mumuni, F Mumuni - Array, 2022‏ - Elsevier
To ensure good performance, modern machine learning models typically require large
amounts of quality annotated data. Meanwhile, the data collection and annotation processes …

A survey of synthetic data augmentation methods in machine vision

A Mumuni, F Mumuni, NK Gerrar - Machine Intelligence Research, 2024‏ - Springer
The standard approach to tackling computer vision problems is to train deep convolutional
neural network (CNN) models using large-scale image datasets that are representative of …

[PDF][PDF] Multimodal image synthesis and editing: A survey

F Zhan, Y Yu, R Wu, J Zhang, S Lu, L Liu… - arxiv preprint arxiv …, 2022‏ - pure.mpg.de
As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

Turning a clip model into a scene text detector

W Yu, Y Liu, W Hua, D Jiang… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
The recent large-scale Contrastive Language-Image Pretraining (CLIP) model has shown
great potential in various downstream tasks via leveraging the pretrained vision and …

Model adaptation: Historical contrastive learning for unsupervised domain adaptation without source data

J Huang, D Guan, A **ao, S Lu - Advances in neural …, 2021‏ - proceedings.neurips.cc
Unsupervised domain adaptation aims to align a labeled source domain and an unlabeled
target domain, but it requires to access the source data which often raises concerns in data …

Auto-regressive image synthesis with integrated quantization

F Zhan, Y Yu, R Wu, J Zhang, K Cui, C Zhang… - European Conference on …, 2022‏ - Springer
Deep generative models have achieved conspicuous progress in realistic image synthesis
with multifarious conditional inputs, while generating diverse yet high-fidelity images …

Unbalanced feature transport for exemplar-based image translation

F Zhan, Y Yu, K Cui, G Zhang, S Lu… - Proceedings of the …, 2021‏ - openaccess.thecvf.com
Despite the great success of GANs in images translation with different conditioned inputs
such as semantic segmentation and edge map, generating high-fidelity images with …

Diverse image inpainting with bidirectional and autoregressive transformers

Y Yu, F Zhan, R Wu, J Pan, K Cui, S Lu, F Ma… - Proceedings of the 29th …, 2021‏ - dl.acm.org
Image inpainting is an underdetermined inverse problem, which naturally allows diverse
contents to fill up the missing or corrupted regions realistically. Prevalent approaches using …

High-resolution image inpainting using multi-scale neural patch synthesis

C Yang, X Lu, Z Lin, E Shechtman… - Proceedings of the …, 2017‏ - openaccess.thecvf.com
Recent advances in deep learning have shown exciting promise in filling large holes in
natural images with semantically plausible and context aware details, impacting …

Mask textspotter v3: Segmentation proposal network for robust scene text spotting

M Liao, G Pang, J Huang, T Hassner, X Bai - Computer Vision–ECCV …, 2020‏ - Springer
Recent end-to-end trainable methods for scene text spotting, integrating detection and
recognition, showed much progress. However, most of the current arbitrary-shape scene text …