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Found 8 papers, 2 papers with code
ECNet: Effective Controllable Text-to-Image Diffusion Models
Secondly, to overcome the issue of limited conditional supervision, we introduce Diffusion Consistency Loss (DCL), which applies supervision on the denoised latent code at any given time step.
AniFaceDrawing: Anime Portrait Exploration during Your Sketching
In the second stage, we simulated the drawing process of the generated images without any additional data (labels) and trained the sketch encoder for incomplete progressive sketches to generate high-quality portrait images with feature alignment to the disentangled representations in the teacher encoder.
Sketch2Cloth: Sketch-based 3D Garment Generation with Unsigned Distance Fields
In this study, we propose Sketch2Cloth, a sketch-based 3D garment generation system using the unsigned distance fields from the user's sketch input.
DiffFaceSketch: High-Fidelity Face Image Synthesis with Sketch-Guided Latent Diffusion Model
We then introduce a Stochastic Region Abstraction (SRA), an approach to augment our dataset to improve the robustness of SGLDM to handle sketch input with arbitrary abstraction.
Stroke Correspondence by Labeling Closed Areas
First, the proposed system separates the closed areas in each keyframe and estimates the correspondences between closed areas by using the characteristics of shape, depth, and closed area connection.
Learning Perceptual Manifold of Fonts
To solve the specific issue, we propose the perceptual manifold of fonts to visualize the perceptual adjustment in the latent space of a generative model of fonts.
dualFace:Two-Stage Drawing Guidance for Freehand Portrait Sketching
In the stage of local guidance, we synthesize detailed portrait images with a deep generative model from user-drawn contour lines, but use the synthesized results as detailed drawing guidance.
Sketch-based Normal Map Generation with Geometric Sampling
This paper proposes a deep generative model for generating normal maps from users sketch with geometric sampling.
