arXiv:2608.23410v1 Announce Type: new
Abstract: Photorealistic novel view synthesis of people remains challenging at high spatial resolutions and across multiple target cameras, where preserving iden...
By Federico Stella, Fei Jiang, Zhongshi Jiang, Zohar Barzelay, Emanuel Garbin, Amin Jourabloo, Liuhao Ge
arXiv:2609.38343v1 Announce Type: new
Abstract: We present SInGA, a novel method for learning Semantic Inpainting for animatable Gaussian head Avatars from a single image. Existing avatar approaches...
By Pilseo Park, Fizza Rubab, Yiying Tong
arXiv:2608.20759v1 Announce Type: new
Abstract: Single-image 3D human reconstruction often suffers from over-smoothed textures and geometric inconsistencies. While diffusion models improve generative...
By Jiakun Li, Li Fang, Hao Zhu, Fei Hu, Long Ye, Yuan Zhang, Jinyao Yan
Spackle is a lightweight residual learning framework designed to improve large-view single-image novel view synthesis (NVS) by mitigating capacity competition in hybrid decoupled systems that combine 3D Gaussian Splatting (3DGS) and diffusion models. It operates in three stages: predicting base 3DGS attributes, automatically identifying poorly reconstructed regions, and learning a residual 3DGS focused on those areas. During inference, Spackle merges the baseline and augmented Gaussians to produce high-fidelity novel views, achieving state‑of‑the‑art performance on large-view-deviation cases.
By Xuanzhi Liu, Yuhe Zhou, Xinyi Wu, Zhenyao Wu, Jinghao Chen, Ruize Han, Song Wang
arXiv:2609.15032v1 Announce Type: new
Abstract: Live free-viewpoint visualization of real humans is critical for immersive communication and interactive digital experiences. Existing methods either r...
By Hanzhang Tu, Zhanfeng Liao, Wei Min, Jiajun Zhang, Yebin Liu
arXiv:2407. 18245v3 Announce Type: replace-cross Abstract: Human head detection, keypoint estimation, and 3D head model fitting are essential tasks with many applications.
By Orest Kupyn, Eugene Khvedchenia, Christian Rupprecht