Probablistic Restoration with Adaptive Noise Sampling for 3D Human Pose Estimation
The accuracy and robustness of 3D human pose estimation (HPE) are limited by 2D pose detection errors and 2D to 3D ill-posed challenges, which have drawn great attention to Multi-Hypothesis HPE research. Most existing MH-HPE methods are based on generative models, which are computationally expensive and difficult to train. In this study, we propose a Probabilistic Restoration 3D Human Pose Estimation framework (PRPose) that can be integrated with any lightweight single-hypothesis model. Specifically, PRPose employs a weakly supervised approach to fit the hidden probability distribution of the 2D-to-3D lifting process in the Single-Hypothesis HPE model and then reverse-map the distribution to the 2D pose input through an adaptive noise sampling strategy to generate reasonable multi-hypothesis samples effectively. Extensive experiments on 3D HPE benchmarks (Human3.6M and MPI-INF-3DHP) highlight the effectiveness and efficiency of PRPose. Code is available at: https://github.com/xzhouzeng/PRPose.
Code (1)
Tasks
3D Human Pose EstimationPose EstimationSimilar Papers 제목 키워드 기반
Adaptive Moments are Surprisingly Effective for Plug-and-Play Diffusion Sampling
Guided diffusion sampling relies on approximating often intractable likelihood scores, which introduces significant noise into the sampling dynamics. We propose using adaptive moment estimation to stabilize these noisy l…
Image RestorationDiffusion Posterior Proximal Sampling for Image Restoration
Diffusion models have demonstrated remarkable efficacy in generating high-quality samples. Existing diffusion-based image restoration algorithms exploit pre-trained diffusion models to leverage data priors, yet they stil…
DenoisingImage RestorationQuality Adaptive Low-Rank Based JPEG Decoding with Applications
Small compression noises, despite being transparent to human eyes, can adversely affect the results of many image restoration processes, if left unaccounted for. Especially, compression noises are highly detrimental to i…
DeblurringImage RestorationQuantizationAll-in-one Weather-degraded Image Restoration via Adaptive Degradation-aware Self-prompting Model
Existing approaches for all-in-one weather-degraded image restoration suffer from inefficiencies in leveraging degradation-aware priors, resulting in sub-optimal performance in adapting to different weather conditions. T…
AllImage ReconstructionImage RestorationEnergy-oriented Diffusion Bridge for Image Restoration with Foundational Diffusion Models
Diffusion bridge models have shown great promise in image restoration by explicitly connecting clean and degraded image distributions. However, they often rely on complex and high-cost trajectories, which limit both samp…
Image Restoration