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Found 5 papers, 3 papers with code
DH-AUG: DH Forward Kinematics Model Driven Augmentation for 3D Human Pose Estimation
To solve this problem, we propose a pose augmentation solution via DH forward kinematics model, which we call DH-AUG. We observe that the previous work is all based on single-frame pose augmentation, if it is directly applied to video pose estimator, there will be several previously ignored problems: (i) angle ambiguity in bone rotation (multiple solutions); (ii) the generated skeleton video lacks movement continuity.
Semi-Supervised 2D Human Pose Estimation Driven by Position Inconsistency Pseudo Label Correction Module
The previous method ignored two problems: (i) When conducting interactive training between large model and lightweight model, the pseudo label of lightweight model will be used to guide large models.
Skeleton2vec: A Self-supervised Learning Framework with Contextualized Target Representations for Skeleton Sequence
In this paper, we show that using high-level contextualized features as prediction targets can achieve superior performance.
Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention
Specifically, we use the gradient attention map (GAM) of the face recognition network to track the sensitive facial regions and make the GAMs of different races tend to be consistent through adversarial learning.
CornerFormer: Boosting Corner Representation for Fine-Grained Structured Reconstruction
Current transformer-based approaches tackle this challenging problem in a two-stage manner, which detect corners in the first model and classify the proposed edges (corner-pairs) in the second model.
