7 citations · 18 across the 9 of their papers we have counts for
10 papers
NBAvatar: Neural Billboards Avatars with Realistic Hand-Face Interaction
David Svitov, Mahtab Dahaghin, Pietro Morerio +1
We present NBAvatar - a method for realistic rendering of head avatars handling non-rigid deformations caused by hand-face interaction. To this end, we introduce a novel hybrid imp…
Frequency-Decomposed Avatar Representation for Varying Camera Distances
David Svitov, Pietro Morerio, Lourdes Agapito +1
We present a CloseUpAvatar - a novel approach for articulated human avatar representation supporting a wider range of camera motions, while preserving rendering quality for close-u…
BillBoard Splatting (BBSplat): Learnable Textured Primitives for Novel View Synthesis
David Svitov, Pietro Morerio, Lourdes Agapito +1
We present billboard Splatting (BBSplat) - a novel approach for novel view synthesis based on textured geometric primitives. BBSplat represents the scene as a set of optimizable te…
HAHA: Highly Articulated Gaussian Human Avatars with Textured Mesh Prior
David Svitov, Pietro Morerio, Lourdes Agapito +1
We present HAHA - a novel approach for animatable human avatar generation from monocular input videos. The proposed method relies on learning the trade-off between the use of Gauss…
MoRF: Mobile Realistic Fullbody Avatars from a Monocular Video
Renat Bashirov, Alexey Larionov, Evgeniya Ustinova +4
We present a system to create Mobile Realistic Fullbody (MoRF) avatars. MoRF avatars are rendered in real-time on mobile devices, learned from monocular videos, and have high reali…
DINAR: Diffusion Inpainting of Neural Textures for One-Shot Human Avatars
David Svitov, Dmitrii Gudkov, Renat Bashirov +1
We present DINAR, an approach for creating realistic rigged fullbody avatars from single RGB images. Similarly to previous works, our method uses neural textures combined with the…
AmphibianDetector: adaptive computation for moving objects detection
David Svitov, Sergey Alyamkin
Convolutional neural networks (CNN) allow achieving the highest accuracy for the task of object detection in images. Major challenges in further development of object detectors are…
MarginDistillation: distillation for margin-based softmax
David Svitov, Sergey Alyamkin
The usage of convolutional neural networks (CNNs) in conjunction with a margin-based softmax approach demonstrates a state-of-the-art performance for the face recognition problem.…
Low-Power Computer Vision: Status, Challenges, Opportunities
Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…
2018 Low-Power Image Recognition Challenge
Sergei Alyamkin, Matthew Ardi, Achille Brighton +38
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technolog…