SOTAVerified

Neural Rendering

Given a representation of a 3D scene of some kind (point cloud, mesh, voxels, etc.), the task is to create an algorithm that can produce photorealistic renderings of this scene from an arbitrary viewpoint. Sometimes, the task is accompanied by image/scene appearance manipulation.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 381–390 of 514 papers

TitleStatusHype
RigNeRF: Fully Controllable Neural 3D Portraits—0
SNeS: Learning Probably Symmetric Neural Surfaces from Incomplete Data—0
SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse ViewsCode2
Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer—0
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields—0
Nerfels: Renderable Neural Codes for Improved Camera Pose Estimation—0
SymFormer: End-to-end symbolic regression using transformer-based architectureCode1
Physically-Based Editing of Indoor Scene Lighting from a Single Image—0
BodyMap: Learning Full-Body Dense Correspondence Map—0
Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers—0
Show:102550
← PrevPage 39 of 52Next →

No leaderboard results yet.