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Remoteclip: A vision language foundation model for remote sensing
General-purpose foundation models have led to recent breakthroughs in artificial
intelligence (AI). In remote sensing, self-supervised learning (SSL) and masked image …
intelligence (AI). In remote sensing, self-supervised learning (SSL) and masked image …
Sam-clip: Merging vision foundation models towards semantic and spatial understanding
The landscape of publicly available vision foundation models (VFMs) such as CLIP and
SAM is expanding rapidly. VFMs are endowed with distinct capabilities stemming from their …
SAM is expanding rapidly. VFMs are endowed with distinct capabilities stemming from their …
AnyLoc: Towards Universal Visual Place Recognition
Visual Place Recognition (VPR) is vital for robot localization. To date, the most performant
VPR approaches are environment-and task-specific: while they exhibit strong performance …
VPR approaches are environment-and task-specific: while they exhibit strong performance …
Lhrs-bot: Empowering remote sensing with vgi-enhanced large multimodal language model
The revolutionary capabilities of large language models (LLMs) have paved the way for
multimodal large language models (MLLMs) and fostered diverse applications across …
multimodal large language models (MLLMs) and fostered diverse applications across …
Scaling self-supervised learning for histopathology with masked image modeling
Computational pathology is revolutionizing the field of pathology by integrating advanced
computer vision and machine learning technologies into diagnostic workflows. It offers …
computer vision and machine learning technologies into diagnostic workflows. It offers …
CROMA: Remote sensing representations with contrastive radar-optical masked autoencoders
A vital and rapidly growing application, remote sensing offers vast yet sparsely labeled,
spatially aligned multimodal data; this makes self-supervised learning algorithms invaluable …
spatially aligned multimodal data; this makes self-supervised learning algorithms invaluable …
Rotary position embedding for vision transformer
Abstract Rotary Position Embedding (RoPE) performs remarkably on language models,
especially for length extrapolation of Transformers. However, the impacts of RoPE on …
especially for length extrapolation of Transformers. However, the impacts of RoPE on …
Reverse engineering self-supervised learning
Understanding the learned representation and underlying mechanisms of Self-Supervised
Learning (SSL) often poses a challenge. In this paper, we 'reverse engineer'SSL, conducting …
Learning (SSL) often poses a challenge. In this paper, we 'reverse engineer'SSL, conducting …
SwitchLight: Co-design of Physics-driven Architecture and Pre-training Framework for Human Portrait Relighting
H Kim, M Jang, W Yoon, J Lee… - Proceedings of the …, 2024 - openaccess.thecvf.com
We introduce a co-designed approach for human portrait relighting that combines a physics-
guided architecture with a pre-training framework. Drawing on the Cook-Torrance …
guided architecture with a pre-training framework. Drawing on the Cook-Torrance …
Know your self-supervised learning: a survey on image-based generative and discriminative training
Although supervised learning has been highly successful in improving the state-of-the-art in
the domain of image-based computer vision in the past, the margin of improvement has …
the domain of image-based computer vision in the past, the margin of improvement has …