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07/15/2023
INVE: Interactive Neural Video Editing
We present Interactive Neural Video Editing (INVE), a real-time video ed...
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05/24/2023
Unsupervised Semantic Correspondence Using Stable Diffusion
Text-to-image diffusion models are now capable of generating images that...
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05/18/2023
PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems
We develop a tool, which we name Protoplanetary Disk Operator Network (P...
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05/12/2023
BlendFields: Few-Shot Example-Driven Facial Modeling
Generating faithful visualizations of human faces requires capturing bot...
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04/24/2023
Pointersect: Neural Rendering with Cloud-Ray Intersection
We propose a novel method that renders point clouds as if they are surfa...
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03/29/2023
CN-DHF: Compact Neural Double Height-Field Representations of 3D Shapes
We introduce CN-DHF (Compact Neural Double-Height-Field), a novel hybrid...
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03/27/2023
FaceLit: Neural 3D Relightable Faces
We propose a generative framework, FaceLit, capable of generating a 3D f...
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12/04/2022
Neural Fourier Filter Bank
We present a novel method to provide efficient and highly detailed recon...
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10/27/2022
Bootstrapping Human Optical Flow and Pose
We propose a bootstrapping framework to enhance human optical flow and p...
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09/21/2022
Attention Beats Concatenation for Conditioning Neural Fields
Neural fields model signals by mapping coordinate inputs to sampled valu...
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08/03/2022
Estimating Visual Information From Audio Through Manifold Learning
We propose a new framework for extracting visual information about a sce...
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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...
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06/16/2022
TUSK: Task-Agnostic Unsupervised Keypoints
Existing unsupervised methods for keypoint learning rely heavily on the ...
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05/27/2022
FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET Imaging
To correct for breathing motion in PET imaging, an interpretable and uns...
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04/29/2022
A Simple Method to Boost Human Pose Estimation Accuracy by Correcting the Joint Regressor for the Human3.6m Dataset
Many human pose estimation methods estimate Skinned Multi-Person Linear ...
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03/23/2022
NeuMan: Neural Human Radiance Field from a Single Video
Photorealistic rendering and reposing of humans is important for enablin...
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01/07/2022
Repurposing Existing Deep Networks for Caption and Aesthetic-Guided Image Cropping
We propose a novel optimization framework that crops a given image based...
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12/03/2021
CoNeRF: Controllable Neural Radiance Fields
We extend neural 3D representations to allow for intuitive and interpret...
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11/24/2021
Layered Controllable Video Generation
We introduce layered controllable video generation, where we, without an...
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11/19/2021
LOLNeRF: Learn from One Look
We present a method for learning a generative 3D model based on neural r...
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06/07/2021
Deep Medial Fields
Implicit representations of geometry, such as occupancy fields or signed...
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03/25/2021
COTR: Correspondence Transformer for Matching Across Images
We propose a novel framework for finding correspondences in images based...
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12/08/2020
Canonical Capsules: Unsupervised Capsules in Canonical Pose
We propose an unsupervised capsule architecture for 3D point clouds. We ...
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11/25/2020
DeRF: Decomposed Radiance Fields
With the advent of Neural Radiance Fields (NeRF), neural networks can no...
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04/15/2020
Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems
Many classical Computer Vision problems, such as essential matrix comput...
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03/25/2020
VaB-AL: Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning
Active Learning for discriminative models has largely been studied with ...
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03/03/2020
Image Matching across Wide Baselines: From Paper to Practice
We introduce a comprehensive benchmark for local features and robust est...
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12/08/2019
VoronoiNet: General Functional Approximators with Local Support
Voronoi diagrams are highly compact representations that are used in var...
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11/25/2019
Reducing the Human Effort in Developing PET-CT Registration
We aim to reduce the tedious nature of developing and evaluating methods...
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09/17/2019
Optimizing Through Learned Errors for Accurate Sports Field Registration
We propose an optimization-based framework to register sports field temp...
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08/15/2019
Beyond Cartesian Representations for Local Descriptors
The dominant approach for learning local patch descriptors relies on sma...
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07/04/2019
Attentive Context Normalization for Robust Permutation-Equivariant Learning
Many problems in computer vision require dealing with sparse, unstructur...
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01/22/2019
Linearized Multi-Sampling for Differentiable Image Transformation
We propose a novel image sampling method for differentiable image transf...
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01/14/2019
Self-Supervised Deep Active Accelerated MRI
We propose to simultaneously learn to sample and reconstruct magnetic re...
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11/26/2018
MIST: Multiple Instance Spatial Transformer Network
We propose a deep network that can be trained to tackle image reconstruc...
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05/24/2018
LF-Net: Learning Local Features from Images
We present a novel deep architecture and a training strategy to learn a ...
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03/21/2018
Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses
Many classical Computer Vision problems, such as essential matrix comput...
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11/16/2017
Learning to Find Good Correspondences
We develop a deep architecture to learn to find good correspondences for...
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09/05/2017
Authoring and Living Next-Generation Location-Based Experiences
Authoring location-based experiences involving multiple participants, co...
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03/30/2016
LIFT: Learned Invariant Feature Transform
We introduce a novel Deep Network architecture that implements the full ...
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11/13/2015
Learning to Assign Orientations to Feature Points
We show how to train a Convolutional Neural Network to assign a canonica...
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11/17/2014
