arXiv AI
Aug 28

Multi-Person Human Motion Forecasting in Complex Scenes

The paper introduces Object-Conditioned Social Diffusion (OCSD), a conditional diffusion model that unifies motion history, multi‑person interactions, and object cues for human motion forecasting in complex scenes. OCSD employs an object‑conditioning mechanism that modulates denoising at each timestep, enabling fine‑grained human‑object reasoning, and a social encoder that captures interactions among all humans. Experiments on the Humans in Kitchens (HiK) and HOI‑M3 benchmarks show state‑of‑the‑art performance, reducing two‑second path error by 31.3% on HiK and 33.2% on HOI‑M3 compared to prior work, while producing more realistic long‑term forecasts.

By Serdar Ozsoy, Lars Doorenbos, Juergen Gall
arXiv AI
Jun 9

HA-VLN 2.0: An Open Benchmark and Leaderboard for Human-Aware Navigation in Discrete and Continuous Environments with Dynamic Multi-Human Interactions

arXiv:2503. 14229v4 Announce Type: replace Abstract: Vision-and-Language Navigation (VLN) has been studied mainly in either discrete or continuous spaces, with little attention to dynamic, crowded environments.

By Yifei Dong, Fengyi Wu, Qi He, Lingdong Kong, Heng Li, Minghan Li, Zebang Cheng, Yuxuan Zhou, Jingdong Sun, Qi Dai, Alexander G Hauptmann, Zhi-Qi Cheng