most citedLPFF: A Portrait Dataset for Face Generators Across Large Poses

1 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Sketch2Human: Deep Human Generation with Disentangled Geometry and Appearance Control

Linzi Qu, Jiaxiang Shang, Hui Ye +2

Geometry- and appearance-controlled full-body human image generation is an interesting but challenging task. Existing solutions are either unconditional or dependent on coarse cond…

cs.CV2024

MonoHair: High-Fidelity Hair Modeling from a Monocular Video

Keyu Wu, Lingchen Yang, Zhiyi Kuang +6

Undoubtedly, high-fidelity 3D hair is crucial for achieving realism, artistic expression, and immersion in computer graphics. While existing 3D hair modeling methods have achieved…

cs.CV20241 cited

CustomSketching: Sketch Concept Extraction for Sketch-based Image Synthesis and Editing

Chufeng Xiao, Hongbo Fu

Personalization techniques for large text-to-image (T2I) models allow users to incorporate new concepts from reference images. However, existing methods primarily rely on textual d…

cs.HC20241 cited

Real-and-Present: Investigating the Use of Life-Size 2D Video Avatars in HMD-Based AR Teleconferencing

Xuanyu Wang, Weizhan Zhang, Christian Sandor +1

Augmented Reality (AR) teleconferencing allows separately located users to interact with each other in 3D through agents in their own physical environments. Existing methods levera…

cs.GR2023

GA-Sketching: Shape Modeling from Multi-View Sketching with Geometry-Aligned Deep Implicit Functions

Jie Zhou, Zhongjin Luo, Qian Yu +2

Sketch-based shape modeling aims to bridge the gap between 2D drawing and 3D modeling by providing an intuitive and accessible approach to create 3D shapes from 2D sketches. Howeve…

cs.CV20231 cited

LPFF: A Portrait Dataset for Face Generators Across Large Poses

Yiqian Wu, Jing Zhang, Hongbo Fu +1

The creation of 2D realistic facial images and 3D face shapes using generative networks has been a hot topic in recent years. Existing face generators exhibit exceptional performan…