4 papers
Camera Control for Text-to-Image Generation via Learning Viewpoint Tokens
Xinxuan Lu, Charless Fowlkes, Alexander C. Berg
Current text-to-image models struggle to provide precise camera control using natural language alone. In this work, we present a framework for precise camera control with global sc…
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…
GViT: Representing Images as Gaussians for Visual Recognition
Jefferson Hernandez, Ruozhen He, Guha Balakrishnan +2
We introduce GVIT, a classification framework that abandons conventional pixel or patch grid input representations in favor of a compact set of learnable 2D Gaussians. Each image i…
Learning from Synthetic Data for Visual Grounding
Ruozhen He, Ziyan Yang, Paola Cascante-Bonilla +2
This paper extensively investigates the effectiveness of synthetic training data to improve the capabilities of vision-and-language models for grounding textual descriptions to ima…