research
∙
09/06/2023
Bayes' Rays: Uncertainty Quantification for Neural Radiance Fields
Neural Radiance Fields (NeRFs) have shown promise in applications like v...
share
research
∙
06/15/2023
Neural Fields with Hard Constraints of Arbitrary Differential Order
While deep learning techniques have become extremely popular for solving...
research
∙
05/24/2023
Unsupervised Semantic Correspondence Using Stable Diffusion
Text-to-image diffusion models are now capable of generating images that...
research
∙
05/12/2023
BlendFields: Few-Shot Example-Driven Facial Modeling
Generating faithful visualizations of human faces requires capturing bot...
research
∙
03/21/2023
CC3D: Layout-Conditioned Generation of Compositional 3D Scenes
In this work, we introduce CC3D, a conditional generative model that syn...
research
∙
02/02/2023
RobustNeRF: Ignoring Distractors with Robust Losses
Neural radiance fields (NeRF) excel at synthesizing new views given mult...
research
∙
11/29/2022
SparsePose: Sparse-View Camera Pose Regression and Refinement
Camera pose estimation is a key step in standard 3D reconstruction pipel...
research
∙
11/28/2022
OpenScene: 3D Scene Understanding with Open Vocabularies
Traditional 3D scene understanding approaches rely on labeled 3D dataset...
research
∙
11/21/2022
NeuMap: Neural Coordinate Mapping by Auto-Transdecoder for Camera Localization
This paper presents an end-to-end neural mapping method for camera local...
research
∙
11/03/2022
nerf2nerf: Pairwise Registration of Neural Radiance Fields
We introduce a technique for pairwise registration of neural fields that...
research
∙
10/13/2022
CUF: Continuous Upsampling Filters
Neural fields have rapidly been adopted for representing 3D signals, but...
research
∙
10/06/2022
Novel View Synthesis with Diffusion Models
We present 3DiM, a diffusion model for 3D novel view synthesis, which is...
research
∙
09/21/2022
Attention Beats Concatenation for Conditioning Neural Fields
Neural fields model signals by mapping coordinate inputs to sampled valu...
research
∙
08/29/2022
Volume Rendering Digest (for NeRF)
Neural Radiance Fields employ simple volume rendering as a way to overco...
research
∙
07/30/2022
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synt...
research
∙
07/20/2022
NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds
We introduce a method for instance proposal generation for 3D point clou...
research
∙
05/31/2022
D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video
Given a monocular video, segmenting and decoupling dynamic objects while...
research
∙
05/09/2022
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
We present Panoptic Neural Fields (PNF), an object-aware neural scene re...
research
∙
12/09/2021
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation
We present Neural Descriptor Fields (NDFs), an object representation tha...
research
∙
12/03/2021
CoNeRF: Controllable Neural Radiance Fields
We extend neural 3D representations to allow for intuitive and interpret...
research
∙
11/29/2021
Urban Radiance Fields
The goal of this work is to perform 3D reconstruction and novel view syn...
research
∙
11/25/2021
NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes
We present NeSF, a method for producing 3D semantic fields from posed RG...
research
∙
11/25/2021
Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations
A classical problem in computer vision is to infer a 3D scene representa...
research
∙
11/25/2021
VaxNeRF: Revisiting the Classic for Voxel-Accelerated Neural Radiance Field
Neural Radiance Field (NeRF) is a popular method in data-driven 3D recon...
research
∙
11/19/2021
LOLNeRF: Learn from One Look
We present a method for learning a generative 3D model based on neural r...
research
∙
08/10/2021
MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision
Recently, huge strides were made in monocular and multi-view pose estima...
research
∙
06/07/2021
Deep Medial Fields
Implicit representations of geometry, such as occupancy fields or signed...
research
∙
04/25/2021
Vector Neurons: A General Framework for SO(3)-Equivariant Networks
Invariance and equivariance to the rotation group have been widely discu...
research
∙
03/25/2021
COTR: Correspondence Transformer for Matching Across Images
We propose a novel framework for finding correspondences in images based...
research
∙
12/18/2020
Human 3D keypoints via spatial uncertainty modeling
We introduce a technique for 3D human keypoint estimation that directly ...
research
∙
12/08/2020
Canonical Capsules: Unsupervised Capsules in Canonical Pose
We propose an unsupervised capsule architecture for 3D point clouds. We ...
research
∙
11/27/2020
Unsupervised part representation by Flow Capsules
Capsule networks are designed to parse an image into a hierarchy of obje...
research
∙
11/25/2020
DeRF: Decomposed Radiance Fields
With the advent of Neural Radiance Fields (NeRF), neural networks can no...
research
∙
10/21/2020
Voronoi Convolutional Neural Networks
In this technical report, we investigate extending convolutional neural ...
research
∙
10/10/2020
LSMAT Least Squares Medial Axis Transform
The medial axis transform has applications in numerous fields including ...
research
∙
06/17/2020
CoSE: Compositional Stroke Embeddings
We present a generative model for stroke-based drawing tasks which is ab...
research
∙
06/14/2020
ShapeFlow: Learnable Deformations Among 3D Shapes
We present ShapeFlow, a flow-based model for learning a deformation spac...
research
∙
05/18/2020
Deep Implicit Volume Compression
We describe a novel approach for compressing truncated signed distance f...
research
∙
04/06/2020
NiLBS: Neural Inverse Linear Blend Skinning
In this technical report, we investigate efficient representations of ar...
research
∙
12/08/2019
VoronoiNet: General Functional Approximators with Local Support
Voronoi diagrams are highly compact representations that are used in var...
research
∙
12/06/2019
NASA: Neural Articulated Shape Approximation
Efficient representation of articulated objects such as human bodies is ...
research
∙
09/12/2019
CvxNets: Learnable Convex Decomposition
Any solid object can be decomposed into a collection of convex polytopes...
research
∙
09/12/2019
CvxNet: Learnable Convex Decomposition
Any solid object can be decomposed into a collection of convex polytopes...
research
∙
07/04/2019
Attentive Context Normalization for Robust Permutation-Equivariant Learning
Many problems in computer vision require dealing with sparse, unstructur...
research
∙
06/12/2019
VIPER: Volume Invariant Position-based Elastic Rods
We extend the formulation of position-based rods to include elastic volu...
research
∙
05/29/2019
Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning
Volumetric (4D) performance capture is fundamental for AR/VR content gen...
research
∙
01/22/2019
Linearized Multi-Sampling for Differentiable Image Transformation
We propose a novel image sampling method for differentiable image transf...
research
∙
11/26/2018
MIST: Multiple Instance Spatial Transformer Network
We propose a deep network that can be trained to tackle image reconstruc...
research
∙
11/16/2017
HandSeg: A Dataset for Hand Segmentation from Depth Images
We introduce a large-scale RGBD hand segmentation dataset, with detailed...
research
∙
05/19/2017