Search Results for author: Jiefeng Li

Found 13 papers, 12 papers with code

D&D: Learning Human Dynamics from Dynamic Camera

1 code implementation19 Sep 2022 Jiefeng Li, Siyuan Bian, Chao Xu, Gang Liu, Gang Yu, Cewu Lu

In this work, we present D&D (Learning Human Dynamics from Dynamic Camera), which leverages the laws of physics to reconstruct 3D human motion from the in-the-wild videos with a moving camera.

3D Human Pose Estimation Human Dynamics

Constructing Balance from Imbalance for Long-tailed Image Recognition

1 code implementation4 Aug 2022 Yue Xu, Yong-Lu Li, Jiefeng Li, Cewu Lu

Previous methods tackle with data imbalance from the viewpoints of data distribution, feature space, and model design, etc. In this work, instead of directly learning a recognition model, we suggest confronting the bottleneck of head-to-tail bias before classifier learning, from the previously omitted perspective of balancing label space.

SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos

2 code implementations27 Dec 2021 Ailing Zeng, Lei Yang, Xuan Ju, Jiefeng Li, Jianyi Wang, Qiang Xu

With a simple yet effective motion-aware fully-connected network, SmoothNet improves the temporal smoothness of existing pose estimators significantly and enhances the estimation accuracy of those challenging frames as a side-effect.

3D Human Pose Estimation 3D Human Reconstruction +1

Localization with Sampling-Argmax

1 code implementation NeurIPS 2021 Jiefeng Li, Tong Chen, Ruiqi Shi, Yujing Lou, Yong-Lu Li, Cewu Lu

In this work, we propose sampling-argmax, a differentiable training method that imposes implicit constraints to the shape of the probability map by minimizing the expectation of the localization error.

3D Human Pose Estimation

Human Pose Regression with Residual Log-likelihood Estimation

3 code implementations ICCV 2021 Jiefeng Li, Siyuan Bian, Ailing Zeng, Can Wang, Bo Pang, Wentao Liu, Cewu Lu

In light of this, we propose a novel regression paradigm with Residual Log-likelihood Estimation (RLE) to capture the underlying output distribution.

3D Human Pose Estimation Multi-Person Pose Estimation

TDAF: Top-Down Attention Framework for Vision Tasks

no code implementations14 Dec 2020 Bo Pang, Yizhuo Li, Jiefeng Li, Muchen Li, Hanwen Cao, Cewu Lu

Such spatial and attention features are nested deeply, therefore, the proposed framework works in a mixed top-down and bottom-up manner.

Action Recognition object-detection +2

CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction

1 code implementation ICCV 2021 Lixin Yang, Xinyu Zhan, Kailin Li, Wenqiang Xu, Jiefeng Li, Cewu Lu

In this paper, we present an explicit contact representation namely Contact Potential Field (CPF), and a learning-fitting hybrid framework namely MIHO to Modeling the Interaction of Hand and Object.

Pose Estimation

HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation

1 code implementation CVPR 2021 Jiefeng Li, Chao Xu, Zhicun Chen, Siyuan Bian, Lixin Yang, Cewu Lu

We show that HybrIK preserves both the accuracy of 3D pose and the realistic body structure of the parametric human model, leading to a pixel-aligned 3D body mesh and a more accurate 3D pose than the pure 3D keypoint estimation methods.

3D human pose and shape estimation Keypoint Estimation

HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation

1 code implementation ECCV 2020 Jiefeng Li, Can Wang, Wentao Liu, Chen Qian, Cewu Lu

The HMOR encodes interaction information as the ordinal relations of depths and angles hierarchically, which captures the body-part and joint level semantic and maintains global consistency at the same time.

3D Multi-Person Pose Estimation (absolute) 3D Multi-Person Pose Estimation (root-relative) +2

CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark

3 code implementations CVPR 2019 Jiefeng Li, Can Wang, Hao Zhu, Yihuan Mao, Hao-Shu Fang, Cewu Lu

In this paper, we propose a novel and efficient method to tackle the problem of pose estimation in the crowd and a new dataset to better evaluate algorithms.

Keypoint Detection Multi-Person Pose Estimation

Pose Flow: Efficient Online Pose Tracking

1 code implementation3 Feb 2018 Yuliang Xiu, Jiefeng Li, Haoyu Wang, Yinghong Fang, Cewu Lu

Multi-person articulated pose tracking in unconstrained videos is an important while challenging problem.

Pose Tracking

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