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Learning Unorthogonalized Matrices for Rotation Estimation
Estimating 3D rotations is a common procedure for 3D computer vision.
On the Calibration of Human Pose Estimation
Most 2D human pose estimation frameworks estimate keypoint confidence in an ad-hoc manner, using heuristics such as the maximum value of heatmaps.
Bias-Compensated Integral Regression for Human Pose Estimation
Experimental results on both the human body and hand benchmarks show that BCIR is faster to train and more accurate than the original integral regression, making it competitive with state-of-the-art detection methods.
Analyzing and Diagnosing Pose Estimation With Attributions
We present Pose Integrated Gradient (PoseIG), the first interpretability technique designed for pose estimation.
Dive Deeper Into Integral Pose Regression
We do a deep dive on the inference and back-propagation of integral pose regression to better understand the causes behind the performance and training differences.
Removing the Bias of Integral Pose Regression
Heatmap-based detection methods are dominant for 2D human pose estimation even though regression is more intuitive.
