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SpatialVLM: Endowing Vision-Language Models with Spatial Reason... TLDR: SpatialVLM is a system that enhances Visual Language Models (VLMs) with spatial reasoning abilities, like understanding distances and sizes in images. ✨ Interactive paper: https://t.co/ucz1clrUti
Generalizable Human Gaussians for Sparse View Synthesis. https://t.co/8KDML09b10
Recent advances in implicit scene representation enable high-fidelity street view novel view synthesis. However, existing methods optimize a neural radiance field for each scene, relying heavily on dense training images and extensive computation resources. To mitigate this… https://t.co/sKTxlN6KKL
Researchers have introduced several new methods in the field of computer vision and artificial intelligence. These include T-VSL for sound localization in videos, ViTamin for vision-language models, MULTIFLOW for efficient Vision-Language models, GraphDreamer for 3D scene synthesis, DNGaussian for creating 3D images, GLiDR for LiDAR navigation, VicTR for video understanding enhancement, OA-CNNs for 3D semantic segmentation, and SpatialVLM for spatial reasoning in Visual Language Models.
