activity
20192026
most citedNeural Style-Preserving Visual Dubbing

63 citations · 198 across the 44 of their papers we have counts for

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Showing 2024Show all

11 papers · 1 filter

cs.CV2024

BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects

Wanyue Zhang, Rishabh Dabral, Vladislav Golyanik +5

We present BimArt, a novel generative approach for synthesizing 3D bimanual hand interactions with articulated objects. Unlike prior works, we do not rely on a reference grasp, a c…

cs.CV2024

Learning to Stabilize Faces

Jan Bednarik, Erroll Wood, Vasileios Choutas +4

Nowadays, it is possible to scan faces and automatically register them with high quality. However, the resulting face meshes often need further processing: we need to stabilize the…

cs.CV2024

EgoAvatar: Egocentric View-Driven and Photorealistic Full-body Avatars

Jianchun Chen, Jian Wang, Yinda Zhang +4

Immersive VR telepresence ideally means being able to interact and communicate with digital avatars that are indistinguishable from and precisely reflect the behaviour of their rea…

cs.CV2024★ 1 cited

FabricDiffusion: High-Fidelity Texture Transfer for 3D Garments Generation from In-The-Wild Clothing Images

Cheng Zhang, Yuanhao Wang, Francisco Vicente Carrasco +4

We introduce FabricDiffusion, a method for transferring fabric textures from a single clothing image to 3D garments of arbitrary shapes. Existing approaches typically synthesize te…

cs.CV2024★ 14 cited

Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures

Marcel C. Bühler, Gengyan Li, Erroll Wood +13

Volumetric modeling and neural radiance field representations have revolutionized 3D face capture and photorealistic novel view synthesis. However, these methods often require hund…

cs.GR2024★ 23 cited

GroomCap: High-Fidelity Prior-Free Hair Capture

Yuxiao Zhou, Menglei Chai, Daoye Wang +5

Despite recent advances in multi-view hair reconstruction, achieving strand-level precision remains a significant challenge due to inherent limitations in existing capture pipeline…