Abstract: Contrastive loss and its variants are very popular for visual representation learning in an unsupervised scenario, where positive and negative pairs are produced to train a feature encoder ...
Constrained Visual Representation Learning With Bisimulation Metrics for Safe Reinforcement Learning
Abstract: Safe reinforcement learning aims to ensure the optimal performance while minimizing potential risks. In real-world applications, especially in scenarios that rely on visual inputs, a key ...
Summary: Researchers discovered how the brain develops reliable visual processing once the eyes open. Early on, visual inputs and modular brain responses are mismatched, creating inconsistent patterns ...
At the ongoing VSLive! developer conference in San Diego, Microsoft today announced Visual Studio 2026 Insiders, a new release of its flagship IDE that pairs deep AI integration with stronger ...
ABSTRACT: The VMamba (Visual State Space Model) is built upon the Mamba model by stacking Visual State Space (VSS) modules and utilizing the 2D Selective Scan (SS2D) module to extend the original ...
The human brain extracts complex information from visual inputs, including objects, their spatial and semantic interrelations, and their interactions with the environment. However, a quantitative ...
In recent years, contrastive language-image models such as CLIP have established themselves as a default choice for learning vision representations, particularly in multimodal applications like Visual ...
Visual generation frameworks follow a two-stage approach: first compressing visual signals into latent representations and then modeling the low-dimensional distributions. However, conventional ...
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