arXiv subjects

Guoliang Wei

Publications and source records attributed to Guoliang Wei.

2 recordsLinked to original sources

arXiv2025

Sleep Modulation: The Challenge of Transitioning from Open Loop to Closed Loop

Sleep disorders have emerged as a critical global health issue, highlighting the urgent need for effective and widely accessible intervention technologies. Non-invasive brain stimulation has garnered attention as it enables direct or indirect modulation of neural activity, thereby promoting sleep enhancement in a safe and unobtrusive manner. This class of approaches is collectively referred to as sleep modulation. To date, the majority of sleep modulation research relies on open-loop paradigms with empirically determined parameters, while achieving individual adaptation and modulation accuracy remains a distant objective. The paradigm-specific constraints inherent to open-loop designs represent a major obstacle to clinical translation and large-scale deployment in home environments. In this paper, we delineate fundamental paradigms of sleep modulation, critically examine the intrinsic limitations of open-loop approaches, and formally conceptualize sleep closed-loop modulation. We further provide a comprehensive synthesis of prior studies involving five commonly employed modulation techniques, evaluating their potential integration within a closed-loop framework. Finally, we identify three primary challenges in constructing an effective sleep closed-loop modulation system: sensor solution selection, monitoring model design, and modulation strategy design, while also proposing potential solutions. Collectively, this work aims to advance the paradigm shift of sleep modulation from open-loop toward closed-loop systems.

cs.HC↗

arXiv2025

HBSplat: Robust Sparse-View Gaussian Reconstruction with Hybrid-Loss Guided Depth and Bidirectional Warping

Novel View Synthesis (NVS) from sparse views presents a formidable challenge in 3D reconstruction, where limited multi-view constraints lead to severe overfitting, geometric distortion, and fragmented scenes. While 3D Gaussian Splatting (3DGS) delivers real-time, high-fidelity rendering, its performance drastically deteriorates under sparse inputs, plagued by floating artifacts and structural failures. To address these challenges, we introduce HBSplat, a unified framework that elevates 3DGS by seamlessly integrating robust structural cues, virtual view constraints, and occluded region completion. Our core contributions are threefold: a Hybrid-Loss Depth Estimation module that ensures multi-view consistency by leveraging dense matching priors and integrating reprojection, point propagation, and smoothness constraints; a Bidirectional Warping Virtual View Synthesis method that enforces substantially stronger constraints by creating high-fidelity virtual views through bidirectional depth-image warping and multi-view fusion; and an Occlusion-Aware Reconstruction component that recovers occluded areas using a depth-difference mask and a learning-based inpainting model. Extensive evaluations on LLFF, Blender, and DTU benchmarks validate that HBSplat sets a new state-of-the-art, achieving up to 21.13 dB PSNR and 0.189 LPIPS, while maintaining real-time inference. Code is available at: https://github.com/eternalland/HBSplat.

cs.CV↗