no code implementations • 7 Feb 2024 • Yash Kant, Ziyi Wu, Michael Vasilkovsky, Guocheng Qian, Jian Ren, Riza Alp Guler, Bernard Ghanem, Sergey Tulyakov, Igor Gilitschenski, Aliaksandr Siarohin
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images.
no code implementations • 24 Oct 2023 • Yash Kant, Aliaksandr Siarohin, Michael Vasilkovsky, Riza Alp Guler, Jian Ren, Sergey Tulyakov, Igor Gilitschenski
Our approach focuses on maximizing the reuse of visible pixels from the source image.
no code implementations • CVPR 2023 • Yash Kant, Aliaksandr Siarohin, Riza Alp Guler, Menglei Chai, Jian Ren, Sergey Tulyakov, Igor Gilitschenski
Next, we combine PIN with a differentiable LBS module to build an expressive and end-to-end Invertible Neural Skinning (INS) pipeline.
2 code implementations • 9 Apr 2021 • Michail Tarasiou, Riza Alp Guler, Stefanos Zafeiriou
For crop type semantic segmentation from Satellite Image Time Series (SITS) we find performance at parcel boundaries to be a critical bottleneck and explain how CSCL tackles the underlying cause of that problem, improving the state-of-the-art performance in this task.
no code implementations • CVPR 2019 • Riza Alp Guler, Iasonas Kokkinos
We introduce HoloPose, a method for holistic monocular 3D human body reconstruction.
Ranked #170 on 3D Human Pose Estimation on Human3.6M
no code implementations • 26 Apr 2019 • Mihir Sahasrabudhe, Zhixin Shu, Edward Bartrum, Riza Alp Guler, Dimitris Samaras, Iasonas Kokkinos
In this work we introduce Lifting Autoencoders, a generative 3D surface-based model of object categories.
no code implementations • ECCV 2018 • Natalia Neverova, Riza Alp Guler, Iasonas Kokkinos
In this work we integrate ideas from surface-based modeling with neural synthesis: we propose a combination of surface-based pose estimation and deep generative models that allows us to perform accurate pose transfer, i. e. synthesize a new image of a person based on a single image of that person and the image of a pose donor.
no code implementations • CVPR 2017 • Riza Alp Guler, Yuxiang Zhou, George Trigeorgis, Epameinondas Antonakos, Patrick Snape, Stefanos Zafeiriou, Iasonas Kokkinos
We define the regression task in terms of the intrinsic, U-V coordinates of a 3D deformable model that is brought into correspondence with image instances at training time.