activity
20142020
most citedMusic-oriented Dance Video Synthesis with Pose Perceptual Loss

18 citations · 27 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20202 cited

Self-supervised Object Tracking with Cycle-consistent Siamese Networks

Weihao Yuan, Michael Yu Wang, Qifeng Chen

Self-supervised learning for visual object tracking possesses valuable advantages compared to supervised learning, such as the non-necessity of laborious human annotations and onli…

cs.CV2020

PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer

Duo Li, Anbang Yao, Qifeng Chen

Despite their strong modeling capacities, Convolutional Neural Networks (CNNs) are often scale-sensitive. For enhancing the robustness of CNNs to scale variance, multi-scale featur…

cs.CV2020

Learning to Learn Parameterized Classification Networks for Scalable Input Images

Duo Li, Anbang Yao, Qifeng Chen

Convolutional Neural Networks (CNNs) do not have a predictable recognition behavior with respect to the input resolution change. This prevents the feasibility of deployment on diff…

cs.CV20203 cited

Active Perception with A Monocular Camera for Multiscopic Vision

Weihao Yuan, Rui Fan, Michael Yu Wang +1

We design a multiscopic vision system that utilizes a low-cost monocular RGB camera to acquire accurate depth estimation for robotic applications. Unlike multi-view stereo with ima…

cs.CV201918 cited

Music-oriented Dance Video Synthesis with Pose Perceptual Loss

Xuanchi Ren, Haoran Li, Zijian Huang +1

We present a learning-based approach with pose perceptual loss for automatic music video generation. Our method can produce a realistic dance video that conforms to the beats and r…

cs.CV2019

Video Depth Estimation by Fusing Flow-to-Depth Proposals

Jiaxin Xie, Chenyang Lei, Zhuwen Li +2

Depth from a monocular video can enable billions of devices and robots with a single camera to see the world in 3D. In this paper, we present an approach with a differentiable flow…