Hyperbolic deep learning in computer vision: A survey
Deep representation learning is a ubiquitous part of modern computer vision. While
Euclidean space has been the de facto standard manifold for learning visual …
Euclidean space has been the de facto standard manifold for learning visual …
GradOrth: a simple yet efficient out-of-distribution detection with orthogonal projection of gradients
Detecting out-of-distribution (OOD) data is crucial for ensuring the safe deployment of
machine learning models in real-world applications. However, existing OOD detection …
machine learning models in real-world applications. However, existing OOD detection …
Up-dp: Unsupervised prompt learning for data pre-selection with vision-language models
In this study, we investigate the task of data pre-selection, which aims to select instances for
labeling from an unlabeled dataset through a single pass, thereby optimizing performance …
labeling from an unlabeled dataset through a single pass, thereby optimizing performance …
VOVTrack: Exploring the Potentiality in Videos for Open-Vocabulary Object Tracking
Open-vocabulary multi-object tracking (OVMOT) represents a critical new challenge
involving the detection and tracking of diverse object categories in videos, encompassing …
involving the detection and tracking of diverse object categories in videos, encompassing …
A streamlined Approach to Multimodal Few-Shot Class Incremental Learning for Fine-Grained Datasets
Few-shot Class-Incremental Learning (FSCIL) poses the challenge of retaining prior
knowledge while learning from limited new data streams, all without overfitting. The rise of …
knowledge while learning from limited new data streams, all without overfitting. The rise of …
Redefining Object Detection for Open-World Settings: A Framework for Simultaneous Identification of Known and Unknown Classes
MA Iqbal, YC Yoon, SK Kim - IEEE Access, 2024 - ieeexplore.ieee.org
Traditional closed-world object detection methods are limited to a predefined set of classes
and struggle to recognize objects beyond these boundaries. This work proposes an …
and struggle to recognize objects beyond these boundaries. This work proposes an …
Hyperbolic Brain Representations
A Joseph, N Francis, M Balay - arXiv preprint arXiv:2409.12990, 2024 - arxiv.org
Artificial neural networks (ANN) were inspired by the architecture and functions of the human
brain and have revolutionised the field of artificial intelligence (AI). Inspired by studies on the …
brain and have revolutionised the field of artificial intelligence (AI). Inspired by studies on the …