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Found 4 papers, 1 papers with code
FDA-GAN: Flow-based Dual Attention GAN for Human Pose Transfer
Human pose transfer aims at transferring the appearance of the source person to the target pose.
GLocal: Global Graph Reasoning and Local Structure Transfer for Person Image Generation
In this paper, we focus on person image generation, namely, generating person image under various conditions, e. g., corrupted texture or different pose.
C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer
Although existing GAN-based HVMT methods have achieved great success, they either fail to preserve appearance details due to the loss of spatial consistency between synthesized and exemplary images, or generate incoherent video results due to the lack of temporal consistency among video frames.
GAC-GAN: A General Method for Appearance-Controllable Human Video Motion Transfer
Therefore, each trained model can only generate videos with a specific scene appearance, new models are required to be trained to generate new appearances.
