no code implementations • 11 Dec 2024 • Shengze Wang, Jiefeng Li, Tianye Li, Ye Yuan, Henry Fuchs, Koki Nagano, Shalini De Mello, Michael Stengel
Extensive experiments on standard benchmarks and real-world close-range images show that our method is the first to accurately recover projection parameters from a single image, and consequently attain state-of-the-art accuracy on 3D pose estimation and 2D alignment for a wide range of images.
no code implementations • 2 Oct 2024 • Junjun Huang, Jifan Wu, Qing Wang, Kemeng Yuan, Jiefeng Li, Di Lu
This paper aims at comparing the time when Hong Kong universities used to ban ChatGPT to the current periods where it has become integrated in the academic processes.
no code implementations • 29 Aug 2024 • Jiefeng Li, Ye Yuan, Davis Rempe, Haotian Zhang, Pavlo Molchanov, Cewu Lu, Jan Kautz, Umar Iqbal
Experiments on three challenging benchmarks demonstrate the effectiveness of COIN, which outperforms the state-of-the-art methods in terms of global human motion estimation and camera motion estimation.
no code implementations • 2 Mar 2024 • Siyuan Bian, Jiefeng Li, Jiasheng Tang, Cewu Lu
Accurate human shape recovery from a monocular RGB image is a challenging task because humans come in different shapes and sizes and wear different clothes.
1 code implementation • 5 Jan 2024 • Jiawei Yang, Katie Z Luo, Jiefeng Li, Congyue Deng, Leonidas Guibas, Dilip Krishnan, Kilian Q Weinberger, Yonglong Tian, Yue Wang
In the second stage, we train a lightweight transformer block to predict clean features from raw ViT outputs, leveraging the derived estimates of the clean features as supervision.
1 code implementation • CVPR 2023 • Jiefeng Li, Siyuan Bian, Qi Liu, Jiasheng Tang, Fan Wang, Cewu Lu
In this work, we present NIKI (Neural Inverse Kinematics with Invertible Neural Network), which models bi-directional errors to improve the robustness to occlusions and obtain pixel-aligned accuracy.
Ranked #1 on
3D Human Pose Estimation
on AGORA
1 code implementation • 12 Apr 2023 • Jiefeng Li, Siyuan Bian, Chao Xu, Zhicun Chen, Lixin Yang, Cewu Lu
To address these issues, this paper presents a novel hybrid inverse kinematics solution, HybrIK, that integrates the merits of 3D keypoint estimation and body mesh recovery in a unified framework.
Ranked #1 on
3D Human Reconstruction
on AGORA
1 code implementation • CVPR 2023 • Qi Fang, Kang Chen, Yinghui Fan, Qing Shuai, Jiefeng Li, Weidong Zhang
Despite various probabilistic methods for modeling the uncertainty and ambiguity in human mesh recovery, their overall precision is limited because existing formulations for joint rotations are either not constrained to SO(3) or difficult to learn for neural networks.
8 code implementations • 7 Nov 2022 • Hao-Shu Fang, Jiefeng Li, Hongyang Tang, Chao Xu, Haoyi Zhu, Yuliang Xiu, Yong-Lu Li, Cewu Lu
Accurate whole-body multi-person pose estimation and tracking is an important yet challenging topic in computer vision.
1 code implementation • 19 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.
1 code implementation • 4 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.
2 code implementations • 27 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.
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.
Ranked #177 on
3D Human Pose Estimation
on Human3.6M
2 code implementations • CVPR 2022 • Kailin Li, Lixin Yang, Xinyu Zhan, Jun Lv, Wenqiang Xu, Jiefeng Li, Cewu Lu
In contrast, data synthesis can easily ensure those diversities separately.
Ranked #3 on
hand-object pose
on HO-3D v2
(using extra training data)
4 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.
Ranked #10 on
Pose Estimation
on COCO val2017
no code implementations • 14 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.
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.
3 code implementations • 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.
Ranked #5 on
3D Human Pose Estimation
on EMDB
no code implementations • 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
1 code implementation • CVPR 2020 • Yong-Lu Li, Xinpeng Liu, Han Lu, Shiyi Wang, Junqi Liu, Jiefeng Li, Cewu Lu
In light of these, we propose a detailed 2D-3D joint representation learning method.
Ranked #1 on
Human-Object Interaction Detection
on Ambiguious-HOI
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.
Ranked #6 on
Multi-Person Pose Estimation
on OCHuman
1 code implementation • 3 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.
Ranked #8 on
Keypoint Detection
on COCO test-challenge