HISR: Hybrid Implicit Surface Representation for Photorealistic 3D Human Reconstruction
원문 초록
Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approaches, however, either represent objects as implicit surface functions or neural volumes and still struggle to recover shapes with heterogeneous materials, in particular human skin, hair or clothes. To this aim, we present a new hybrid implicit surface representation to model human shapes. This representation is composed of two surface layers that represent opaque and translucent regions on the clothed human body. We segment different regions automatically using visual cues and learn to reconstruct two signed distance functions (SDFs). We perform surface-based rendering on opaque regions (e.g., body, face, clothes) to preserve high-fidelity surface normals and volume rendering on translucent regions (e.g., hair). Experiments demonstrate that our approach obtains state-of-the-art results on 3D human reconstructions, and also shows competitive performances on other objects.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds
HumanGif: Single-View Human Diffusion with Generative Prior
Efficient Neural Implicit Representation for 3D Human Reconstruction
Multi-hypotheses Conditioned Point Cloud Diffusion for 3D Human Reconstruction from Occluded Images
Joint Reconstruction of 3D Human and Object via Contact-Based Refinement Transformer
Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot
토론
이 논문과 연결된 포럼 글이 아직 없습니다.