Collaborative Representation Learning for Alignment of Tactile, Language, and Vision Modalities

A robot has learned to lip sync by observing YouTube videos, addressing a significant challenge in robotics where humanoids often struggle with realistic lip movements during conversations. This advancement highlights the importance of lip motion in human interaction, which constitutes nearly half of the attention during face-to-face communication.

The Multimodal Visual Geometry Grounded Transformer (MVGGT) has been introduced as a novel framework for Multiview 3D Referring Expression Segmentation (MV-3DRES), addressing the limitations of existing methods that depend on dense point clouds. MVGGT enables segmentation directly from sparse multi-view images, enhancing efficiency and performance in real-world applications.