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20192022
most citedTFPose: Direct Human Pose Estimation with Transformers

57 citations · 110 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV20227 cited

Contact-aware Human Motion Forecasting

Wei Mao, Miaomiao Liu, Richard Hartley +1

In this paper, we tackle the task of scene-aware 3D human motion forecasting, which consists of predicting future human poses given a 3D scene and a past human motion. A key challe…

cs.CV20221 cited

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Wei Mao, Miaomiao Liu, Mathieu Salzmann

We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short mot…

cs.CV20229 cited

Remember Intentions: Retrospective-Memory-based Trajectory Prediction

Chenxin Xu, Weibo Mao, Wenjun Zhang +1

To realize trajectory prediction, most previous methods adopt the parameter-based approach, which encodes all the seen past-future instance pairs into model parameters. However, in…

cs.CV20214 cited

Multi-level Motion Attention for Human Motion Prediction

Wei Mao, Miaomiao Liu, Mathieu Salzmann +1

Human motion prediction aims to forecast future human poses given a historical motion. Whether based on recurrent or feed-forward neural networks, existing learning based methods f…

cs.CV20212 cited

FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutions

Weian Mao, Zhi Tian, Xinlong Wang +1

We propose a fully convolutional multi-person pose estimation framework using dynamic instance-aware convolutions, termed FCPose. Different from existing methods, which often requi…

cs.CV202157 cited

TFPose: Direct Human Pose Estimation with Transformers

Weian Mao, Yongtao Ge, Chunhua Shen +3

We propose a human pose estimation framework that solves the task in the regression-based fashion. Unlike previous regression-based methods, which often fall behind those state-of-…