[AIGC&CG进展] 上海科技大学、Deemos提出DreamFace,仅通过文本控制生成个性化的3D人脸,并可以支持人脸老化、化妆或通过视频进行人脸动画控制 04:14 [Diffusion生成NeRF] TUM, Apple提出HyperDiffusion,用Diffusion计算神经场权重,统一框架下生成3D权重或4D动画 03:19 [NeRF Relighting进展,SIGGRAPH] 浙大、微软亚研...
[AIGC&CG进展] 上海科技大学、Deemos提出DreamFace,仅通过文本控制生成个性化的3D人脸,并可以支持人脸老化、化妆或通过视频进行人脸动画控制 04:14 [Diffusion生成NeRF] TUM, Apple提出HyperDiffusion,用Diffusion计算神经场权重,统一框架下生成3D权重或4D动画 03:19 [NeRF Relighting进展,SIGGRAPH] 浙大、微软亚研...
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models (NeurIPS 2023) Abstract The ability to create high-quality 3D faces from a single image has become in- creasingly important with wide applications in video conferencing, AR/VR, and advanced video edi...
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models (NeurIPS 2023) Abstract The ability to create high-quality 3D faces from a single image has become in- creasingly important with wide applications in video conferencing, AR/VR, and advanced video edi...
and compute efficiency. Further, we show that our method serves as a unified solution for both reflective and non-reflective scenes, going beyond the previous alternatives focusing on only reflective scenes. Also, we illustrate that Ref- Gaussian supports more applications such as relighting and edit...
T. NeRV: Neural reflectance and visibility fields for relighting and view synthesis.CVPR (2021). SHN19 Saito S., Huang Z., Natsume R., Morishima S., Kanazawa A., Li H. Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization.In Proceedings of the International ...
Relighting Neural Radiance Fields with Shadow and Highlight Hints https://arxiv.org/abs/2308.13404 浙江大学、微软亚洲研究院、College of William & Mary 本文提出了一种新的神经隐式辐射率表示,用于从由与视图位置不同的移动点光源照亮的物体的一小组非结构化照片中进行自由视点重新照明 ...
Moreover, our method can be extended to enable 3D-aware real portrait relighting. Through extensive quantitative and qualitative evaluations, we demonstrate the superior 3D-aware lighting control ability of our model compared to alternative and existing solutions.KAIWEN JIANG...
Though this improves quality, both NeRF and mip-NeRF struggle when dealing with unbounded scenes, where the camera may face any direction and scene con- tent may exist at any distance. In this work, we present an extension to mip-NeRF we call "mip-NeRF 360" that ...
In the fu- ture, we will further explore the combination of relighting methods. After editing the scene geometry, the correspond- ing colors can be modified to make the light and shadow in the rendering results more natural. In future work, we will implement our proposed app...