The paper introduces Doppio, a new video dataset of falling ground coffee with per‑frame weight measurements, aimed at enabling contactless mass estimation via computer vision. The authors evaluate several deep learning models—spatial feed‑forward networks and recurrent spatio‑temporal architectures—to predict the cumulative weight of the falling particles. Results show that these models can accurately estimate weight, suggesting a viable, low‑cost alternative to traditional contact‑based measurement systems.
By Simon Kiefhaber, Jan-Martin O. Steitz, Julia Grabinski, Christoph Reich, Paul Wagner, Max Zimmermann, Simone Schaub-Meyer, Stefan Roth
PACT is an end‑to‑end model that jointly learns human pose, contacts, and contact forces from monocular video. It augments a human reconstruction foundation model with learnable contact‑force tokens and a temporal transformer, and uses physics‑based supervision to enforce consistency between motion and forces. The authors also create a data annotation pipeline and a real‑world climbing benchmark, ForceWall, to train and evaluate the system, achieving state‑of‑the‑art performance and better generalization than staged approaches.
By Rikhat Akizhanov (MBZUAI), Yangsong Zhang (MBZUAI), Nikolai Kaliazin (MBZUAI), Peter Wolf (ETH Z\"urich), Yoshihiko Nakamura (MBZUAI), Pascal Fua (EPFL), Fabio Pizzati (MBZUAI), Ivan Laptev (MBZUAI)
Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic range, and low power consumption. While many studies and datasets in neuromorphic vision have focused on automotive and drone applications, human-centric daily-life scenarios remain largely underrepresented, despite their importance for developing and benchmarking event-based perception systems.
arXiv:2610.13242v1 Announce Type: new
Abstract: Currently, the animal production sector is undergoing rapid development of techniques that allow automatic monitoring of animal behaviour and health. T...
By Sebastian Puchala, Dominik Gronkiewicz, Marcin Go{\l}\k{e}biewski, Grzegorz Grodkowski, Grzegorz Gwardys
arXiv:2607. 12909v1 Announce Type: cross Abstract: Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static pose classification or discrete temporal pattern matching, fundamentally overlooking the instability dynamics of the human support system.
By Wenjun Xia, Zhicheng Peng, Haopeng Li, Zhengdi Zhang
arXiv:2510. 26369v2 Announce Type: replace Abstract: Logistics warehouses have struggled with labor shortages, but the inbound processes remain particularly human-powered.
By Kazuma Kano, Yuki Mori, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi