27 citations · 34 across the 9 of their papers we have counts for
9 papers · 1 filter
Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories
Wonbong Jang, Shikun Liu, Soubhik Sanyal +6
Recovering camera parameters from images and rendering scenes from novel viewpoints have been treated as separate tasks in computer vision and graphics. This separation breaks down…
TransText: Alpha-as-RGB Representation for Transparent Text Animation
Fei Zhang, Zijian Zhou, Bohao Tang +9
We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic v…
Generative Zoo
Tomasz Niewiadomski, Anastasios Yiannakidis, Hanz Cuevas-Velasquez +4
The model-based estimation of 3D animal pose and shape from images enables computational modeling of animal behavior. Training models for this purpose requires large amounts of lab…
RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-plane Networks
Partha Ghosh, Soubhik Sanyal, Cordelia Schmid +1
We present a novel unconditional video generative model designed to address long-term spatial and temporal dependencies, with attention to computational and dataset efficiency. To…
Synthesizing Environment-Specific People in Photographs
Mirela Ostrek, Carol O'Sullivan, Michael J. Black +1
We present ESP, a novel method for context-aware full-body generation, that enables photo-realistic synthesis and inpainting of people wearing clothing that is semantically appropr…
SCULPT: Shape-Conditioned Unpaired Learning of Pose-dependent Clothed and Textured Human Meshes
Soubhik Sanyal, Partha Ghosh, Jinlong Yang +3
We present SCULPT, a novel 3D generative model for clothed and textured 3D meshes of humans. Specifically, we devise a deep neural network that learns to represent the geometry and…
Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency
Soubhik Sanyal, Alex Vorobiov, Timo Bolkart +5
Synthesizing images of a person in novel poses from a single image is a highly ambiguous task. Most existing approaches require paired training images; i.e. images of the same pers…
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Soubhik Sanyal, Timo Bolkart, Haiwen Feng +1
The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions. Robustness requires a larg…
Generating 3D faces using Convolutional Mesh Autoencoders
Anurag Ranjan, Timo Bolkart, Soubhik Sanyal +1
Learned 3D representations of human faces are useful for computer vision problems such as 3D face tracking and reconstruction from images, as well as graphics applications such as…