
Ep#21 TesserAct: Learning 4D Embodied World Models
RoboPapers
00:00
Exploring 4D Scene Representation and Robotics
This chapter examines the limitations of models that generate 4D scene representations from single-view video inputs, particularly their inability to produce multi-view data for complete reconstructions. It also highlights recent advancements in robotics, including the integration of URE5 robots and the importance of data quality in training world models. The discussion underscores the interplay between innovative research, complex datasets, and the future of robotic capabilities.
Transcript
Play full episode