no code implementations • 15 Jun 2023 • Lap Chi Lau, Kam Chuen Tung, Robert Wang
We consider a new semidefinite programming relaxation for directed edge expansion, which is obtained by adding triangle inequalities to the reweighted eigenvalue formulation.
no code implementations • 3 May 2023 • Lap Chi Lau, Robert Wang, Hong Zhou
We prove that a randomized local search approach provides a unified algorithm to solve this problem for all $p$.
no code implementations • ICCV 2023 • Mathias Parger, Chengcheng Tang, Thomas Neff, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
Moving cameras add new challenges in how to fuse newly unveiled image regions with already processed regions efficiently to minimize the update rate - without increasing memory overhead and without knowing the camera extrinsics of future frames.
no code implementations • 17 Nov 2022 • Lap Chi Lau, Kam Chuen Tung, Robert Wang
The first main result is a Cheeger inequality relating the vertex expansion $\vec{\psi}(G)$ of a directed graph $G$ to the vertex-capacitated maximum reweighted second eigenvalue $\vec{\lambda}_2^{v*}$: \[ \vec{\lambda}_2^{v*} \lesssim \vec{\psi}(G) \lesssim \sqrt{\vec{\lambda}_2^{v*} \cdot \log (\Delta/\vec{\lambda}_2^{v*})}.
no code implementations • 31 Oct 2022 • Shangchen Han, Po-Chen Wu, Yubo Zhang, Beibei Liu, Linguang Zhang, Zheng Wang, Weiguang Si, Peizhao Zhang, Yujun Cai, Tomas Hodan, Randi Cabezas, Luan Tran, Muzaffer Akbay, Tsz-Ho Yu, Cem Keskin, Robert Wang
In this paper, we present a unified end-to-end differentiable framework for multi-view, multi-frame hand tracking that directly predicts 3D hand pose in world space.
no code implementations • 18 Oct 2022 • Mathias Parger, Chengcheng Tang, Thomas Neff, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
Moving cameras add new challenges in how to fuse newly unveiled image regions with already processed regions efficiently to minimize the update rate - without increasing memory overhead and without knowing the camera extrinsics of future frames.
no code implementations • 30 Jul 2022 • Lin Huang, Tomas Hodan, Lingni Ma, Linguang Zhang, Luan Tran, Christopher Twigg, Po-Chen Wu, Junsong Yuan, Cem Keskin, Robert Wang
Unlike classical correspondence-based methods which predict 3D object coordinates at pixels of the input image, the proposed method predicts 3D object coordinates at 3D query points sampled in the camera frustum.
1 code implementation • CVPR 2022 • Fadime Sener, Dibyadip Chatterjee, Daniel Shelepov, Kun He, Dipika Singhania, Robert Wang, Angela Yao
Assembly101 is a new procedural activity dataset featuring 4321 videos of people assembling and disassembling 101 "take-apart" toy vehicles.
no code implementations • CVPR 2022 • Mathias Parger, Chengcheng Tang, Christopher D. Twigg, Cem Keskin, Robert Wang, Markus Steinberger
With DeltaCNN, we present a sparse convolutional neural network framework that enables sparse frame-by-frame updates to accelerate video inference in practice.
1 code implementation • ICCV 2021 • Manuel Kaufmann, Yi Zhao, Chengcheng Tang, Lingling Tao, Christopher Twigg, Jie Song, Robert Wang, Otmar Hilliges
To this end, we present a method to estimate SMPL parameters from 6-12 EM sensors.
no code implementations • 12 Nov 2020 • Mathias Parger, Chengcheng Tang, Yuanlu Xu, Christopher Twigg, Lingling Tao, Yijing Li, Robert Wang, Markus Steinberger
Tracking body and hand motions in the 3D space is essential for social and self-presence in augmented and virtual environments.
no code implementations • CVPR 2020 • Edoardo Remelli, Shangchen Han, Sina Honari, Pascal Fua, Robert Wang
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras.
Ranked #4 on 3D Human Pose Estimation on Total Capture
1 code implementation • 7 Feb 2018 • Abhronil Sengupta, Yuting Ye, Robert Wang, Chiao Liu, Kaushik Roy
Over the past few years, Spiking Neural Networks (SNNs) have become popular as a possible pathway to enable low-power event-driven neuromorphic hardware.