activity
20172022
most citedDeepFake Detection Based on the Discrepancy Between the Face and its Context

28 citations · 48 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2022★ 3 cited

FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment

Yuval Nirkin, Yosi Keller, Tal Hassner

We present Face Swapping GAN (FSGAN) for face swapping and reenactment. Unlike previous work, we offer a subject agnostic swapping scheme that can be applied to pairs of faces with…

cs.CV2020

HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation

Yuval Nirkin, Lior Wolf, Tal Hassner

We present a novel, real-time, semantic segmentation network in which the encoder both encodes and generates the parameters (weights) of the decoder. Furthermore, to allow maximal…

cs.CV2020★ 28 cited

DeepFake Detection Based on the Discrepancy Between the Face and its Context

Yuval Nirkin, Lior Wolf, Yosi Keller +1

We propose a method for detecting face swapping and other identity manipulations in single images. Face swapping methods, such as DeepFake, manipulate the face region, aiming to ad…

cs.CV2019

FSGAN: Subject Agnostic Face Swapping and Reenactment

Yuval Nirkin, Yosi Keller, Tal Hassner

We present Face Swapping GAN (FSGAN) for face swapping and reenactment. Unlike previous work, FSGAN is subject agnostic and can be applied to pairs of faces without requiring train…

cs.CV2017★ 4 cited

Extreme 3D Face Reconstruction: Seeing Through Occlusions

Anh Tuan Tran, Tal Hassner, Iacopo Masi +3

Existing single view, 3D face reconstruction methods can produce beautifully detailed 3D results, but typically only for near frontal, unobstructed viewpoints. We describe a system…

cs.CV2017★ 13 cited

On Face Segmentation, Face Swapping, and Face Perception

Yuval Nirkin, Iacopo Masi, Anh Tuan Tran +2

We show that even when face images are unconstrained and arbitrarily paired, face swapping between them is actually quite simple. To this end, we make the following contributions.…