11 citations · 28 across the 8 of their papers we have counts for
10 papers · 1 filter
CoNFies: Controllable Neural Face Avatars
Heng Yu, Koichiro Niinuma, Laszlo A. Jeni
Neural Radiance Fields (NeRF) are compelling techniques for modeling dynamic 3D scenes from 2D image collections. These volumetric representations would be well suited for synthesi…
MBW: Multi-view Bootstrapping in the Wild
Mosam Dabhi, Chaoyang Wang, Tim Clifford +3
Labeling articulated objects in unconstrained settings have a wide variety of applications including entertainment, neuroscience, psychology, ethology, and many fields of medicine.…
Instantaneous Physiological Estimation using Video Transformers
Ambareesh Revanur, Ananyananda Dasari, Conrad S. Tucker +1
Video-based physiological signal estimation has been limited primarily to predicting episodic scores in windowed intervals. While these intermittent values are useful, they provide…
Deep Implicit Surface Point Prediction Networks
Rahul Venkatesh, Tejan Karmali, Sarthak Sharma +4
Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit repr…
3D Human Pose, Shape and Texture from Low-Resolution Images and Videos
Xiangyu Xu, Hao Chen, Francesc Moreno-Noguer +2
3D human pose and shape estimation from monocular images has been an active research area in computer vision. Existing deep learning methods for this task rely on high-resolution i…
DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces
Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh +2
High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classic…