3 papers
cs.CV2026
GoDe: Gaussians on Demand for Progressive Level of Detail and Scalable Compression
Francesco Di Sario, Riccardo Renzulli, Marco Grangetto +2
Recent progress in compressing explicit radiance field representations, particularly 3D Gaussian Splatting, has substantially reduced memory consumption while improving real-time r…
cs.CV2026
SAGA: Learning Signal-Aligned Distributions for Improved Text-to-Image Generation
Paul Grimal, Michaël Soumm, Hervé Le Borgne +2
State-of-the-art text-to-image models produce visually impressive results but often struggle with precise alignment to text prompts, leading to missing critical elements or uninten…
cs.CV2024
NEMO: Can Multimodal LLMs Identify Attribute-Modified Objects?
Jiaxuan Li, Junwen Mo, MinhDuc Vo +2
Multimodal Large Language Models (MLLMs) have made notable advances in visual understanding, yet their abilities to recognize objects modified by specific attributes remain an open…