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20172021
most citedNeural Rerendering in the Wild

9 citations · 11 across the 2 of their papers we have counts for

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5 papers · 1 filter

cs.CV2021

Learned Spatial Representations for Few-shot Talking-Head Synthesis

Moustafa Meshry, Saksham Suri, Larry S. Davis +1

We propose a novel approach for few-shot talking-head synthesis. While recent works in neural talking heads have produced promising results, they can still produce images that do n…

cs.CV2021

StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis

Moustafa Meshry, Yixuan Ren, Larry S Davis +1

We propose a novel approach for multi-modal Image-to-image (I2I) translation. To tackle the one-to-many relationship between input and output domains, previous works use complex tr…

cs.CV20199 cited

Neural Rerendering in the Wild

Moustafa Meshry, Dan B Goldman, Sameh Khamis +4

We explore total scene capture -- recording, modeling, and rerendering a scene under varying appearance such as season and time of day. Starting from internet photos of a tourist l…

cs.CV2018

Two Stream Self-Supervised Learning for Action Recognition

Ahmed Taha, Moustafa Meshry, Xitong Yang +2

We present a self-supervised approach using spatio-temporal signals between video frames for action recognition. A two-stream architecture is leveraged to tangle spatial and tempor…

cs.CV20172 cited

Texture Synthesis with Recurrent Variational Auto-Encoder

Rohan Chandra, Sachin Grover, Kyungjun Lee +2

We propose a recurrent variational auto-encoder for texture synthesis. A novel loss function, FLTBNK, is used for training the texture synthesizer. It is rotational and partially c…