Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...

Abstract: Deep learning models in computer vision face challenges such as high computational resource demands and limited generalization in practical scenarios. To address these issues, this study ...

Abstract: Vision Transformer (ViT) is an image recognition model that uses transformer architecture, which has a numerous advantage over Convolution Neural Networks (CNN). It offers improved accuracy, ...

[Dennis] of [Made by Dennis] has been building a Voron 0 for fun and education, and since this apparently wasn’t enough of a challenge, decided to add a number of scratch-built improvements and ...

Ethical disclosures and Gaussian Splatting are on the wane, while the sheer volume of submitted papers represents a new problem for AI to tackle in 2026. Opinion I have followed computer vision and ...