Tootfinder

LIPM-Guided Reinforcement Learning for Stable and Perceptive Locomotion in Bipedal Robots
Haokai Su, Haoxiang Luo, Shunpeng Yang, Kaiwen Jiang, Wei Zhang, Hua Chen
https://arxiv.org/abs/2509.09106

LIPM-Guided Reinforcement Learning for Stable and Perceptive Locomotion in Bipedal Robots
Achieving stable and robust perceptive locomotion for bipedal robots in unstructured outdoor environments remains a critical challenge due to complex terrain geometry and susceptibility to external disturbances. In this work, we propose a novel reward design inspired by the Linear Inverted Pendulum Model (LIPM) to enable perceptive and stable locomotion in the wild. The LIPM provides theoretical guidance for dynamic balance by regulating the center of mass (CoM) height and the torso orientation…

MMDEW: Multipurpose Multiclass Density Estimation in the Wild
Villanelle O'Reilly, Jonathan Cox, Georgios Leontidis, Marc Hanheide, Petra Bosilj, James Brown
https://arxiv.org/abs/2510.02213

MMDEW: Multipurpose Multiclass Density Estimation in the Wild
Density map estimation can be used to estimate object counts in dense and occluded scenes where discrete counting-by-detection methods fail. We propose a multicategory counting framework that leverages a Twins pyramid vision-transformer backbone and a specialised multi-class counting head built on a state-of-the-art multiscale decoding approach. A two-task design adds a segmentation-based Category Focus Module, suppressing inter-category cross-talk at training time. Training and evaluation on t…

This Obsidian theme is wild! I don't see myself using it full-time, but I love having it among my options. :smug:
#obsidian

GitHub - emarpiee/Retroma: Retroma is an Obsidian theme that blends nostalgic, classic design with an intelligent color scheme algorithm.
Retroma is an Obsidian theme that blends nostalgic, classic design with an intelligent color scheme algorithm. - emarpiee/Retroma

Dancing with a Robot: An Experimental Study of Child-Robot Interaction in a Performative Art Setting
Victor Ngo, Rachel, Ramchurn, Roma Patel, Alan Chamberlain, Ayse Kucukyilmaz
https://arxiv.org/abs/2508.05208

Dancing with a Robot: An Experimental Study of Child-Robot Interaction in a Performative Art Setting
This paper presents an evaluation of 18 children's in-the-wild experiences with the autonomous robot arm performer NED (Never-Ending Dancer) within the Thingamabobas installation, showcased across the UK. We detail NED's design, including costume, behaviour, and human interactions, all integral to the installation. Our observational analysis revealed three key challenges in child-robot interactions: 1) Initiating and maintaining engagement, 2) Lack of robot expressivity and reciprocity, and 3) …

WaveSP-Net: Learnable Wavelet-Domain Sparse Prompt Tuning for Speech Deepfake Detection
Xi Xuan, Xuechen Liu, Wenxin Zhang, Yi-Cheng Lin, Xiaojian Lin, Tomi Kinnunen
https://arxiv.org/abs/2510.05305

WaveSP-Net: Learnable Wavelet-Domain Sparse Prompt Tuning for Speech Deepfake Detection
Modern front-end design for speech deepfake detection relies on full fine-tuning of large pre-trained models like XLSR. However, this approach is not parameter-efficient and may lead to suboptimal generalization to realistic, in-the-wild data types. To address these limitations, we introduce a new family of parameter-efficient front-ends that fuse prompt-tuning with classical signal processing transforms. These include FourierPT-XLSR, which uses the Fourier Transform, and two variants based on …

3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review
Salma Galaaoui, Eduardo Valle, David Picard, Nermin Samet
https://arxiv.org/abs/2509.12197 https://

3D Human Pose and Shape Estimation from LiDAR Point Clouds: A Review
In this paper, we present a comprehensive review of 3D human pose estimation and human mesh recovery from in-the-wild LiDAR point clouds. We compare existing approaches across several key dimensions, and propose a structured taxonomy to classify these methods. Following this taxonomy, we analyze each method's strengths, limitations, and design choices. In addition, (i) we perform a quantitative comparison of the three most widely used datasets, detailing their characteristics; (ii) we compile u…