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Found 5 papers, 1 papers with code
Deep Learning for 3D Human Pose Estimation and Mesh Recovery: A Survey
To the best of our knowledge, this survey is arguably the first to comprehensively cover deep learning methods for 3D human pose estimation, including both single-person and multi-person approaches, as well as human mesh recovery, encompassing methods based on explicit models and implicit representations.
An atrium segmentation network with location guidance and siamese adjustment
The segmentation of atrial scan images is of great significance for the three-dimensional reconstruction of the atrium and the surgical positioning.
Face Forgery Detection Based on Facial Region Displacement Trajectory Series
We introduce a method for detecting manipulated videos that is based on the trajectory of the facial region displacement.
Automatic segmentation of meniscus based on MAE self-supervision and point-line weak supervision paradigm
Medical image segmentation based on deep learning is often faced with the problems of insufficient datasets and long time-consuming labeling.
FakeTransformer: Exposing Face Forgery From Spatial-Temporal Representation Modeled By Facial Pixel Variations
With the rapid development of generation model, AI-based face manipulation technology, which called DeepFakes, has become more and more realistic.
