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Found 5 papers, 1 papers with code
Contrastive Vision-Language Pre-training with Limited Resources
However, these works require a tremendous amount of data and computational resources (e. g., billion-level web data and hundreds of GPUs), which prevent researchers with limited resources from reproduction and further exploration.
Person-in-Context Synthesiswith Compositional Structural Space
To handle the stark difference in input structures, we proposed two separate neural branches to attentively composite the respective (context/person) inputs into shared ``compositional structural space'', which encodes shape, location and appearance information for both context and person structures in a disentangled manner.
Instance-level Facial Attributes Transfer with Geometry-Aware Flow
Geometry-aware flow is able to warp the source face attribute into the target face context and generate a warp-and-blend result.
Image Generation from Layout
The representation of each object is disentangled into a specified/certain part (category) and an unspecified/uncertain part (appearance).
Ranked #2 on
Layout-to-Image Generation
on Visual Genome 64x64
Semi-Latent GAN: Learning to generate and modify facial images from attributes
Generating and manipulating human facial images using high-level attributal controls are important and interesting problems.
