7 citations · 26 across the 18 of their papers we have counts for
33 papers · 1 filter
ViPS: Video-informed Pose Spaces for Auto-Rigged Meshes
Honglin Chen, Karran Pandey, Rundi Wu +6
Kinematic rigs provide a structured interface for articulating 3D meshes but lack any associated pose space, i.e., an explicit representation of the plausible manifold of joint con…
Faster 3D Gaussian Splatting Convergence via Structure-Aware Densification
Linjie Lyu, Ayush Tewari, Jianchun Chen +2
3D Gaussian Splatting has emerged as a powerful scene representation for real-time novel-view synthesis. However, its standard adaptive density control relies on screen-space posit…
Understanding Multi-View Transformers
Michal Stary, Julien Gaubil, Ayush Tewari +1
Multi-view transformers such as DUSt3R are revolutionizing 3D vision by solving 3D tasks in a feed-forward manner. However, contrary to previous optimization-based pipelines, the i…
Manifold Sampling for Differentiable Uncertainty in Radiance Fields
Linjie Lyu, Ayush Tewari, Marc Habermann +4
Radiance fields are powerful and, hence, popular models for representing the appearance of complex scenes. Yet, constructing them based on image observations gives rise to ambiguit…
GAURA: Generalizable Approach for Unified Restoration and Rendering of Arbitrary Views
Vinayak Gupta, Rongali Simhachala Venkata Girish, Mukund Varma T +2
Neural rendering methods can achieve near-photorealistic image synthesis of scenes from posed input images. However, when the images are imperfect, e.g., captured in very low-light…
FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent
Cameron Smith, David Charatan, Ayush Tewari +1
This paper introduces FlowMap, an end-to-end differentiable method that solves for precise camera poses, camera intrinsics, and per-frame dense depth of a video sequence. Our metho…