Training a computer vision model on a 50:50 blend of synthetic and real eye images produces more reliable segmentation of the ...

US-DATA, a data annotation company specializing in machine learning and computer vision projects, announces the expansion of ...

Abstract: This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour ...

Abstract: This paper investigates one of the most fundamental computer vision problems: image segmentation. We propose a supervised hierarchical approach to object-independent image segmentation.

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

The official code repo for the paper Stochastic Segmentation with Conditional Categorical Diffusion Models, accepted at the International Conference on Computer Vision (ICCV) 2023. Semantic ...

Recent developments in materials science have made it possible to synthesize millions of individual nanoparticles on a chip. However, many steps in the characterization process still require extensive ...

Abstract: Recent advances in foundational Vision Language Models (VLMs) have reshaped the evaluation paradigm in computer vision tasks. These foundational models, especially CLIP, have accelerated ...

1 Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China. 2 Landing Artificial Intelligence Center for Pathological Diagnosis, Wuhan University, Wuhan, China.

Computer vision, a branch of artificial intelligence, centers on training devices to recognize and perceive visual information. This field involves a variety of techniques to transform ...

Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition ...