Sparse and noisy millimeter-wave radar point cloud observations often correspond to multiple plausible human poses, making deterministic pose estimation fundamentally ill-posed. Yet existing radar methods remain deterministic, collapsing this ambiguity into a single estimate.
arXiv:2609.34220v2 Announce Type: replace-cross
Abstract: Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as ob...
By Junqiao Fan, Yuxuan Hu, Bofan Lyu, Yanshuo Lu, Pengfei Liu, Jiarui Zhang, Fangqiang Ding, Lihua Xie, Gen Li, Jianfei Yang
The paper introduces SoundMHPE, an encoder‑decoder framework that estimates 3D poses of multiple people using only acoustic signals. It addresses challenges such as overlapping acoustic signatures and inter‑person reflections by employing a multi‑scale acoustic encoder and a temporal pose decoder with attention. The authors created the 6‑hour Acoustic Multi‑person Pose (AMP) dataset and show that SoundMHPE outperforms baseline models.
By Yusuke Oumi, Yuto Shibata, Go Irie, Akisato Kimura, Yoshimitsu Aoki, Mariko Isogawa
Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as object delivery. However, most existing HRI systems rely on R...
arXiv:2607. 04541v1 Announce Type: cross Abstract: Camera-radar (CR) fusion is a practical sensing configuration for autonomous driving, but existing models are typically trained with task-specific supervision, limiting reusable representation learning.
By Jingyu Song, Yi Liu, Katherine A. Skinner
arXiv:2608. 15815v1 Announce Type: new Abstract: WiFi Channel State Information (CSI) has emerged as a privacy-preserving alternative to cameras for human pose estimation.
By Quang-Anh N. D., Duc Pham Minh, Thao Phuong Pham, Minh Anh Nguyen, Huan X. Nguyen, Tuan Dang