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20172023
most citedSketch-pix2seq: a Model to Generate Sketches of Multiple Categories

45 citations · 67 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023

PFB-Diff: Progressive Feature Blending Diffusion for Text-driven Image Editing

Wenjing Huang, Shikui Tu, Lei Xu

Diffusion models have demonstrated their ability to generate diverse and high-quality images, sparking considerable interest in their potential for real image editing applications.…

cs.CV2022

Linking Sketch Patches by Learning Synonymous Proximity for Graphic Sketch Representation

Sicong Zang, Shikui Tu, Lei Xu

Graphic sketch representations are effective for representing sketches. Existing methods take the patches cropped from sketches as the graph nodes, and construct the edges based on…

cs.CV20221 cited

IA-FaceS: A Bidirectional Method for Semantic Face Editing

Wenjing Huang, Shikui Tu, Lei Xu

Semantic face editing has achieved substantial progress in recent years. Known as a growingly popular method, latent space manipulation performs face editing by changing the latent…

cs.CV20211 cited

Deep Rival Penalized Competitive Learning for Low-resolution Face Recognition

Peiying Li, Shikui Tu, Lei Xu

Current face recognition tasks are usually carried out on high-quality face images, but in reality, most face images are captured under unconstrained or poor conditions, e.g., by v…

cs.CV2018

Computational Decomposition of Style for Controllable and Enhanced Style Transfer

Minchao Li, Shikui Tu, Lei Xu

Neural style transfer has been demonstrated to be powerful in creating artistic image with help of Convolutional Neural Networks (CNN). However, there is still lack of computationa…

cs.CV201745 cited

Sketch-pix2seq: a Model to Generate Sketches of Multiple Categories

Yajing Chen, Shikui Tu, Yuqi Yi +1

Sketch is an important media for human to communicate ideas, which reflects the superiority of human intelligence. Studies on sketch can be roughly summarized into recognition and…