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Found 3 papers, 1 papers with code
SEFD: Learning to Distill Complex Pose and Occlusion
This paper addresses the problem of three-dimensional (3D) human mesh estimation in complex poses and occluded situations.
Ranked #1 on
2D Human Pose Estimation
on OCHuman
Self-Supervised Depth Estimation with Isometric-Self-Sample-Based Learning
Most previous methods have alleviated this issue by removing the dynamic regions in the photometric loss formulation based on the masks estimated from another module, making it difficult to fully utilize the training images.
Propose-and-Attend Single Shot Detector
We present a simple yet effective prediction module for a one-stage detector.
