Papers with Code 아카이브
Multi-Hypotheses 3D Human Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis Aggregation
GFPose: Learning 3D Human Pose Prior with Gradient Fields
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild
Probabilistic Modeling for Human Mesh Recovery
Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows
Probabilistic 3D Human Shape and Pose Estimation from Multiple Unconstrained Images in the Wild
3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image Data
GraphMDN: Leveraging graph structure and deep learning to solve inverse problems
Weakly Supervised Generative Network for Multiple 3D Human Pose Hypotheses
Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network
Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
End-to-end Recovery of Human Shape and Pose
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.