A review on machine learning styles in computer vision—techniques and future directions

SV Mahadevkar, B Khemani, S Patil, K Kotecha… - Ieee …, 2022 - ieeexplore.ieee.org
Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …

Advances and challenges in meta-learning: A technical review

A Vettoruzzo, MR Bouguelia… - IEEE transactions on …, 2024 - ieeexplore.ieee.org
Meta-learning empowers learning systems with the ability to acquire knowledge from
multiple tasks, enabling faster adaptation and generalization to new tasks. This review …

Multimodal foundation models: From specialists to general-purpose assistants

C Li, Z Gan, Z Yang, J Yang, L Li… - … and Trends® in …, 2024 - nowpublishers.com
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Blind image quality assessment via vision-language correspondence: A multitask learning perspective

W Zhang, G Zhai, Y Wei, X Yang… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
We aim at advancing blind image quality assessment (BIQA), which predicts the human
perception of image quality without any reference information. We develop a general and …

Perceiver io: A general architecture for structured inputs & outputs

A Jaegle, S Borgeaud, JB Alayrac, C Doersch… - ar**s for multi-task learning
C Fifty, E Amid, Z Zhao, T Yu… - Advances in Neural …, 2021 - proceedings.neurips.cc
Multi-task learning can leverage information learned by one task to benefit the training of
other tasks. Despite this capacity, naively training all tasks together in one model often …

Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans

A Eftekhar, A Sax, J Malik… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Computer vision now relies on data, but we know surprisingly little about what factors in the
data affect performance. We argue that this stems from the way data is collected. Designing …