9 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
Continual Zero-Shot Learning through Semantically Guided Generative Random Walks
Wenxuan Zhang, Paul Janson, Kai Yi +2
Learning novel concepts, remembering previous knowledge, and adapting it to future tasks occur simultaneously throughout a human's lifetime. To model such comprehensive abilities,…
SATR: Zero-Shot Semantic Segmentation of 3D Shapes
Ahmed Abdelreheem, Ivan Skorokhodov, Maks Ovsjanikov +1
We explore the task of zero-shot semantic segmentation of 3D shapes by using large-scale off-the-shelf 2D image recognition models. Surprisingly, we find that modern zero-shot 2D o…
StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2
Ivan Skorokhodov, Sergey Tulyakov, Mohamed Elhoseiny
Videos show continuous events, yet most if not all video synthesis frameworks treat them discretely in time. In this work, we think of videos of what they should be tim…
Aligning Latent and Image Spaces to Connect the Unconnectable
Ivan Skorokhodov, Grigorii Sotnikov, Mohamed Elhoseiny
In this work, we develop a method to generate infinite high-resolution images with diverse and complex content. It is based on a perfectly equivariant generator with synchronous in…
Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation
Divyansh Jha, Kai Yi, Ivan Skorokhodov +1
We propose a novel loss for generative models, dubbed as GRaWD (Generative Random Walk Deviation), to improve learning representations of unexplored visual spaces. Quality learning…
Adversarial Generation of Continuous Images
Ivan Skorokhodov, Savva Ignatyev, Mohamed Elhoseiny
In most existing learning systems, images are typically viewed as 2D pixel arrays. However, in another paradigm gaining popularity, a 2D image is represented as an implicit neural…