8 papers · 1 filter
Joint Optimization for 4D Human-Scene Reconstruction in the Wild
Zhizheng Liu, Joe Lin, Wayne Wu +1
Reconstructing human motion and its surrounding environment is crucial for understanding human-scene interaction and predicting human movements in the scene. While much progress ha…
From Seeing to Experiencing: Scaling Navigation Foundation Models with Reinforcement Learning
Honglin He, Yukai Ma, Brad Squicciarini +2
Navigation foundation models trained on massive web-scale data enable agents to generalize across diverse environments and embodiments. However, these models, which are trained sol…
Visually-grounded Humanoid Agents
Hang Ye, Xiaoxuan Ma, Fan Lu +3
Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively animated, relying on privil…
UrbanVerse: Scaling Urban Simulation by Watching City-Tour Videos
Mingxuan Liu, Honglin He, Elisa Ricci +2
Urban embodied AI agents, ranging from delivery robots to quadrupeds, are increasingly populating our cities, navigating chaotic streets to provide last-mile connectivity. Training…
Towards Autonomous Micromobility through Scalable Urban Simulation
Wayne Wu, Honglin He, Chaoyuan Zhang +5
Micromobility, which utilizes lightweight mobile machines moving in urban public spaces, such as delivery robots and mobility scooters, emerges as a promising alternative to vehicu…
Vid2Sim: Realistic and Interactive Simulation from Video for Urban Navigation
Ziyang Xie, Zhizheng Liu, Zhenghao Peng +2
Sim-to-real gap has long posed a significant challenge for robot learning in simulation, preventing the deployment of learned models in the real world. Previous work has primarily…