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20182023
most citedDrag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

205 citations · 240 across the 16 of their papers we have counts for

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Showing cs.CVShow all

19 papers · 1 filter

cs.CV2023★ 3 cited

HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image

Tong Wu, Zhibing Li, Shuai Yang +5

3D content creation from a single image is a long-standing yet highly desirable task. Recent advances introduce 2D diffusion priors, yielding reasonable results. However, existing…

cs.CV2023★ 3 cited

MATLABER: Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR

Xudong Xu, Zhaoyang Lyu, Xingang Pan +1

Based on powerful text-to-image diffusion models, text-to-3D generation has made significant progress in generating compelling geometry and appearance. However, existing methods st…

cs.CV2023

AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatars

Mohit Mendiratta, Xingang Pan, Mohamed Elgharib +6

Capturing and editing full head performances enables the creation of virtual characters with various applications such as extended reality and media production. The past few years…

cs.CV2023★ 205 cited

Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

Xingang Pan, Ayush Tewari, Thomas Leimkühler +3

Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existin…

cs.CV2023★ 1 cited

GVP: Generative Volumetric Primitives

Mallikarjun B R, Xingang Pan, Mohamed Elgharib +1

Advances in 3D-aware generative models have pushed the boundary of image synthesis with explicit camera control. To achieve high-resolution image synthesis, several attempts have b…

cs.CV2023★ 2 cited

HQ3DAvatar: High Quality Controllable 3D Head Avatar

Kartik Teotia, Mallikarjun B R, Xingang Pan +4

Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynami…