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Found 10 papers, 6 papers with code
View-Consistent 4D Light Field Superpixel Segmentation
Many 4D light field processing applications rely on superpixel segmentations, for which occlusion-aware view consistency is important.
View-consistent 4D Light Field Depth Estimation
Previous light field depth estimation methods typically estimate a depth map only for the central sub-aperture view, and struggle with view consistent estimation.
Differentiable Diffusion for Dense Depth Estimation from Multi-view Images
We present a method to estimate dense depth by optimizing a sparse set of points such that their diffusion into a depth map minimizes a multi-view reprojection error from RGB supervision.
Edge-aware Bidirectional Diffusion for Dense Depth Estimation from Light Fields
We present an algorithm to estimate fast and accurate depth maps from light fields via a sparse set of depth edges and gradients.
Neural Fields in Visual Computing and Beyond
Recent advances in machine learning have created increasing interest in solving visual computing problems using a class of coordinate-based neural networks that parametrize physical properties of scenes or objects across space and time.
Temporally Consistent Online Depth Estimation Using Point-Based Fusion
The presence of dynamic objects further complicates the problem.
Tiled Multiplane Images for Practical 3D Photography
Based on the observation that the depth complexity in local image regions is lower than that over the entire image, we split an MPI into many small, tiled regions, each with only a few depth planes.
GauFRe: Gaussian Deformation Fields for Real-time Dynamic Novel View Synthesis
We propose a method for dynamic scene reconstruction using deformable 3D Gaussians that is tailored for monocular video.
TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusion
In contrast, TextureDreamer can transfer highly detailed, intricate textures from real-world environments to arbitrary objects with only a few casually captured images, potentially significantly democratizing texture creation.
ReplaceAnything3D:Text-Guided 3D Scene Editing with Compositional Neural Radiance Fields
We introduce ReplaceAnything3D model (RAM3D), a novel text-guided 3D scene editing method that enables the replacement of specific objects within a scene.
