12 citations · 23 across the 8 of their papers we have counts for
11 papers · 1 filter
SceNeRFlow: Time-Consistent Reconstruction of General Dynamic Scenes
Edith Tretschk, Vladislav Golyanik, Michael Zollhoefer +3
Existing methods for the 4D reconstruction of general, non-rigidly deforming objects focus on novel-view synthesis and neglect correspondences. However, time consistency enables ad…
Neural Lens Modeling
Wenqi Xian, Aljaž Božič, Noah Snavely +1
Recent methods for 3D reconstruction and rendering increasingly benefit from end-to-end optimization of the entire image formation process. However, this approach is currently limi…
SSDNeRF: Semantic Soft Decomposition of Neural Radiance Fields
Siddhant Ranade, Christoph Lassner, Kai Li +4
Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function. This is achieved by using an MLP together with a mapping to a higher-…
Self-supervised Neural Articulated Shape and Appearance Models
Fangyin Wei, Rohan Chabra, Lingni Ma +6
Learning geometry, motion, and appearance priors of object classes is important for the solution of a large variety of computer vision problems. While the majority of approaches ha…
Virtual Elastic Objects
Hsiao-yu Chen, Edgar Tretschk, Tuur Stuyck +4
We present Virtual Elastic Objects (VEOs): virtual objects that not only look like their real-world counterparts but also behave like them, even when subject to novel interactions.…
ANR: Articulated Neural Rendering for Virtual Avatars
Amit Raj, Julian Tanke, James Hays +3
The combination of traditional rendering with neural networks in Deferred Neural Rendering (DNR) provides a compelling balance between computational complexity and realism of the r…