Browsing: Hugging Face
The integration of long-context capabilities with visual understanding unlocks unprecedented potential for Vision Language Models (VLMs). However, the quadratic attention…
Global healthcare providers are exploring use of large language models (LLMs) to provide medical advice to the public. LLMs now…
We introduce CameraBench, a large-scale dataset and benchmark designed to assess and improve camera motion understanding. CameraBench consists of ~3,000…
Given a single labeled example, in-context segmentation aims to segment corresponding objects. This setting, known as one-shot segmentation in few-shot…
Dimensionality reduction techniques are fundamental for analyzing and visualizing high-dimensional data. With established methods like t-SNE and PCA presenting a…
In recent years, image editing models have witnessed remarkable and rapid development. The recent unveiling of cutting-edge multimodal models such…
Despite the rapid growth of machine learning research, corresponding code implementations are often unavailable, making it slow and labor-intensive for…
The Contrastive Language-Image Pre-training (CLIP) framework has become a widely used approach for multimodal representation learning, particularly in image-text retrieval…
Visit our project page at: https://apc-vlm.github.io/ 🙂 Abstract:We present a framework for perspective-aware reasoning in vision-language models (VLMs) through mental…
Autoregressive patch-based image generation has recently shown competitive results in terms of image quality and scalability. It can also be…