Browsing: AI News
Unified vision-language models have emerged as a frontier, blending the visual with the verbal to create models that can interpret images and respond in human language.…
Google researchers address the challenges of achieving a comprehensive understanding of diverse video content by introducing a novel encoder model, VideoPrism. Existing models in video understanding…
Point clouds serve as a prevalent representation of 3D data, with the extraction of point-wise features being crucial for various tasks related to 3D understanding. While…
Multimodal Large Language Models (MLLMs), having contributed to remarkable progress in AI, face challenges in accurately processing and responding to misleading information, leading to incorrect or…
The evolution of Vision Language Models (VLMs) towards general-purpose models relies on their ability to understand images and perform tasks via natural language instructions. However, it…
The introduction of Augmented Reality (AR) and wearable Artificial Intelligence (AI) gadgets is a significant advancement in human-computer interaction. With AR and AI gadgets facilitating data…
In 3D reconstruction and generation, pursuing techniques that balance visual richness with computational efficiency is paramount. Effective methods such as Gaussian Splatting often have significant limitations,…
Text-to-image (T2I) and text-to-video (T2V) generation have made significant strides in generative models. While T2I models can control subject identity well, extending this capability to T2V…
Deep learning has revolutionized view synthesis in computer vision, offering diverse approaches like NeRF and end-to-end style architectures. Traditionally, 3D modeling methods like voxels, point clouds,…
MoD-SLAM is a state-of-the-art method for Simultaneous Localization And Mapping (SLAM) systems. In SLAM systems, it is challenging to achieve real-time, accurate, and scalable dense mapping.…