AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
A lightweight Spectral-Hypergraph Fusion Network (SHFPose) is proposed, which provides an efficient approach for modeling structural priors in single-image 3D human pose estimation, and shows potential value for real-time and edge-oriented applications.
This paper proposes a lightweight high-resolution pose estimation network, UG-HRNet, which significantly reduces model complexity while maintaining competitive performance, serving as a practical alternative to existing popular lightweight networks.
Recovering 3D digital humans from a single 2D image is an ill-posed computer vision problem due to the loss of depth information. Probabilistic 3D human pose estimation compensates for this by estimating a set of 3D hypotheses from a prior distribution via generative models. However, most prior work focuses only on 3D...
CL-HPE is presented, a lightweight framework for competitive and efficient pose estimation that provides a practical solution in resource-constrained environments and suggests a favorable accuracy–efficiency trade-off among lightweight pose estimators.
DiMMPose is proposed, a diffusion-based framework enhanced by Mamba’s state-space model for robust and efficient 3D pose estimation, which combines structured prompts encoded by LongCLIP with learnable prompt representations to provide anatomical and motion-related guidance during denoising.
Transformers have become dominant in 3D Human Pose Estimation (HPE). However, existing Transformer-based 3D HPE backbones often encounter a trade-off between accuracy and computational efficiency. To resolve the above dilemma, in this work we leverage recent advances in state space models and utilize Mamba for high-qua...
Monocular 3D human pose estimation (HPE) remains challenging due to depth ambiguity, occlu- sions, and the need for temporal consistency. While multi-view methods provide superior accuracy over monocular approaches, they often require complex setups. We introduce STA-TFM, a transformer-based architecture that combines...
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