Co-occurring keywords · papers mentioning both
Papers
LTM: Lightweight Textured Mesh Extraction and Refinement of Large Unbounded Scenes for Efficient Storage and Real-time Rendering
CVPR 2024
Multi-task Learning with 3D-Aware Regularization
ICLR 2024
NeISF: Neural Incident Stokes Field for Geometry and Material Estimation
CVPR 2024
Neural 3D Strokes: Creating Stylized 3D Scenes with Vectorized 3D Strokes
CVPR 2024
Neural Textured Deformable Meshes for Robust Analysis-by-Synthesis
WACV 2024
Optimize & Reduce: A Top-Down Approach for Image Vectorization
AAAI 2024
PhyRecon: Physically Plausible Neural Scene Reconstruction
NeurIPS 2024
Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models
CVPR 2024
QUADify: Extracting Meshes with Pixel-level Details and Materials from Images
CVPR 2024
R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction
NeurIPS 2024
Relightable and Animatable Neural Avatar from Sparse-View Video
CVPR 2024
Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction
CoRL 2024
Specular Object Reconstruction Behind Frosted Glass by Differentiable Rendering
WACV 2024
Subsurface Scattering for Gaussian Splatting
NeurIPS 2024
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering
WACV 2024
Tetrahedron Splatting for 3D Generation
NeurIPS 2024
Towards Realistic Generative 3D Face Models
WACV 2024
TutteNet: Injective 3D Deformations by Composition of 2D Mesh Deformations
CVPR 2024
UniPAD: A Universal Pre-training Paradigm for Autonomous Driving
CVPR 2024
VINECS: Video-based Neural Character Skinning
CVPR 2024
3D Shape Reconstruction of Semi-Transparent Worms
CVPR 2023
Accidental Light Probes
CVPR 2023
A Theory of Topological Derivatives for Inverse Rendering of Geometry
ICCV 2023
A Unified Spatial-Angular Structured Light for Single-View Acquisition of Shape and Reflectance
CVPR 2023
Chasing Clouds: Differentiable Volumetric Rasterisation of Point Clouds as a Highly Efficient and Accurate Loss for Large-Scale Deformable 3D Registration
ICCV 2023