6 citations · 17 across the 6 of their papers we have counts for
21 papers
Disentangling Content and Motion for Text-Based Neural Video Manipulation
Levent Karacan, Tolga Kerimoğlu, İsmail İnan +3
Giving machines the ability to imagine possible new objects or scenes from linguistic descriptions and produce their realistic renderings is arguably one of the most challenging pr…
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
Alp Yurtsever, Tolga Birdal, Vladislav Golyanik
We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-FW, for solving quadratic, linearly-constrained, binary optimization problems on quantum annea…
HuMoR: 3D Human Motion Model for Robust Pose Estimation
Davis Rempe, Tolga Birdal, Aaron Hertzmann +3
We introduce HuMoR: a 3D Human Motion Model for Robust Estimation of temporal pose and shape. Though substantial progress has been made in estimating 3D human motion and shape from…
Weakly Supervised Learning of Rigid 3D Scene Flow
Zan Gojcic, Or Litany, Andreas Wieser +2
We propose a data-driven scene flow estimation algorithm exploiting the observation that many 3D scenes can be explained by a collection of agents moving as rigid bodies. At the co…
MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization
Jiahui Huang, He Wang, Tolga Birdal +4
We present MultiBodySync, a novel, end-to-end trainable multi-body motion segmentation and rigid registration framework for multiple input 3D point clouds. The two non-trivial chal…
Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation
Haowen Deng, Mai Bui, Nassir Navab +3
In this work, we introduce Deep Bingham Networks (DBN), a generic framework that can naturally handle pose-related uncertainties and ambiguities arising in almost all real life app…