Search Results for author: Yoni Kasten

Found 16 papers, 9 papers with code

Text2LIVE: Text-Driven Layered Image and Video Editing

1 code implementation5 Apr 2022 Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman, Yoni Kasten, Tali Dekel

Given an input image or video and a target text prompt, our goal is to edit the appearance of existing objects (e. g., object's texture) or augment the scene with visual effects (e. g., smoke, fire) in a semantically meaningful manner.

Layered Neural Atlases for Consistent Video Editing

2 code implementations23 Sep 2021 Yoni Kasten, Dolev Ofri, Oliver Wang, Tali Dekel

We present a method that decomposes, or "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video.

Style Transfer Video Reconstruction +1

Volume Rendering of Neural Implicit Surfaces

1 code implementation NeurIPS 2021 Lior Yariv, Jiatao Gu, Yoni Kasten, Yaron Lipman

Accurate sampling is important to provide a precise coupling of geometry and radiance; and (iii) it allows efficient unsupervised disentanglement of shape and appearance in volume rendering.

Disentanglement Inductive Bias

Deep Permutation Equivariant Structure from Motion

1 code implementation ICCV 2021 Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri

Existing deep methods produce highly accurate 3D reconstructions in stereo and multiview stereo settings, i. e., when cameras are both internally and externally calibrated.

Matrix Completion

End-To-End Convolutional Neural Network for 3D Reconstruction of Knee Bones From Bi-Planar X-Ray Images

no code implementations2 Apr 2020 Yoni Kasten, Daniel Doktofsky, Ilya Kovler

In contrast to the common approach of statistically modeling the shape of each bone, our deep network learns the distribution of the bones' shapes directly from the training images.

3D Reconstruction Style Transfer

Frequency Bias in Neural Networks for Input of Non-Uniform Density

no code implementations ICML 2020 Ronen Basri, Meirav Galun, Amnon Geifman, David Jacobs, Yoni Kasten, Shira Kritchman

Recent works have partly attributed the generalization ability of over-parameterized neural networks to frequency bias -- networks trained with gradient descent on data drawn from a uniform distribution find a low frequency fit before high frequency ones.

The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies

1 code implementation NeurIPS 2019 Ronen Basri, David Jacobs, Yoni Kasten, Shira Kritchman

We study the relationship between the frequency of a function and the speed at which a neural network learns it.

Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings

no code implementations ICCV 2019 Yoni Kasten, Amnon Geifman, Meirav Galun, Ronen Basri

A common approach to essential matrix averaging is to separately solve for camera orientations and subsequently for camera positions.

Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches

1 code implementation27 Jan 2019 Yoni Kasten, Meirav Galun, Ronen Basri

In this paper, we introduce a novel solution to the six-point online algorithm to recover the exterior parameters associated with $I_n$.

GPSfM: Global Projective SFM Using Algebraic Constraints on Multi-View Fundamental Matrices

1 code implementation CVPR 2019 Yoni Kasten, Amnon Geifman, Meirav Galun, Ronen Basri

First, given ${n \choose 2}$ fundamental matrices computed for $n$ images, we provide a complete algebraic characterization in the form of conditions that are both necessary and sufficient to enabling the recovery of camera matrices.

Two view constraints on the epipoles from few correspondences

no code implementations22 Oct 2018 Yoni Kasten, Michael Werman

We show how it can be used to reduce the number of required points for the epipolar geometry when some information about the epipoles is available and demonstrate this with a buddy search app.

Fundamental Matrices from Moving Objects Using Line Motion Barcodes

no code implementations26 Jul 2016 Yoni Kasten, Gil Ben-Artzi, Shmuel Peleg, Michael Werman

Corresponding epipolar lines have similar motion barcodes, and candidate pairs of corresponding epipoar lines are found by the similarity of their motion barcodes.

Camera Calibration from Dynamic Silhouettes Using Motion Barcodes

no code implementations CVPR 2016 Gil Ben-Artzi, Yoni Kasten, Shmuel Peleg, Michael Werman

The use of motion barcodes leads to increased speed, accuracy, and robustness in computing the epipolar geometry.

Camera Calibration

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