1 code implementation • 6 Jan 2025 • Yuxiang Bao, Guoliang Kang, Linlin Yang, Xiaoyue Duan, Bo Zhao, Baochang Zhang
Differently, in this paper, we identify that the bias towards the frequent class may be encoded into features, i. e., the rare-specific features which play a key role in discriminating the rare class are much weaker than the frequent-specific features.
1 code implementation • 29 May 2024 • Yuguang Yang, Runtang Guo, Sheng Wu, Yimi Wang, Linlin Yang, Bo Fan, Jilong Zhong, Juan Zhang, Baochang Zhang
Interpreting complex deep networks, notably pre-trained vision-language models (VLMs), is a formidable challenge.
no code implementations • 5 Apr 2024 • Jiayin Zhu, Linlin Yang, Angela Yao
We present InstructHumans, a novel framework for instruction-driven 3D human texture editing.
2 code implementations • 25 Mar 2024 • Zicong Fan, Takehiko Ohkawa, Linlin Yang, Nie Lin, Zhishan Zhou, Shihao Zhou, Jiajun Liang, Zhong Gao, Xuanyang Zhang, Xue Zhang, Fei Li, Zheng Liu, Feng Lu, Karim Abou Zeid, Bastian Leibe, Jeongwan On, Seungryul Baek, Aditya Prakash, Saurabh Gupta, Kun He, Yoichi Sato, Otmar Hilliges, Hyung Jin Chang, Angela Yao
A holistic 3Dunderstanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation.
1 code implementation • 25 Aug 2023 • Jiayin Zhu, Zhuoran Zhao, Linlin Yang, Angela Yao
We present HiFiHR, a high-fidelity hand reconstruction approach that utilizes render-and-compare in the learning-based framework from a single image, capable of generating visually plausible and accurate 3D hand meshes while recovering realistic textures.
no code implementations • CVPR 2023 • Ziwei Yu, Chen Li, Linlin Yang, Xiaoxu Zheng, Michael Bi Mi, Gim Hee Lee, Angela Yao
However, the reconstructed meshes are prone to artifacts and do not appear as plausible hand shapes.
no code implementations • 25 Jan 2023 • Kerui Gu, Linlin Yang, Michael Bi Mi, Angela Yao
Experimental results on both the human body and hand benchmarks show that BCIR is faster to train and more accurate than the original integral regression, making it competitive with state-of-the-art detection methods.
1 code implementation • 21 Jan 2023 • Shihao Zhang, Linlin Yang, Michael Bi Mi, Xiaoxu Zheng, Angela Yao
In computer vision, it is often observed that formulating regression problems as a classification task often yields better performance.
Ranked #19 on
Crowd Counting
on ShanghaiTech B
no code implementations • CVPR 2023 • Qiuxia Lin, Linlin Yang, Angela Yao
To solve this problem, we present a framework for cross-domain semi-supervised hand pose estimation and target the challenging scenario of learning models from labelled multi-modal synthetic data and unlabelled real-world data.
no code implementations • CVPR 2023 • Qiyuan He, Linlin Yang, Kerui Gu, Qiuxia Lin, Angela Yao
We present Pose Integrated Gradient (PoseIG), the first interpretability technique designed for pose estimation.
1 code implementation • ICCV 2023 • Rongyu Chen, Linlin Yang, Angela Yao
For monocular RGB-based 3D pose and shape estimation, multiple solutions are often feasible due to factors like occlusion and truncation.
Ranked #1 on
Multi-Hypotheses 3D Human Pose Estimation
on AH36M
no code implementations • 24 Nov 2022 • Ziwei Yu, Linlin Yang, You Xie, Ping Chen, Angela Yao
We propose a novel framework for 3D hand shape reconstruction and hand-object grasp optimization from a single RGB image.
Ranked #5 on
3D Hand Pose Estimation
on HO-3D v3
no code implementations • 17 Mar 2022 • Runqi Wang, Linlin Yang, Baochang Zhang, Wentao Zhu, David Doermann, Guodong Guo
Research on the generalization ability of deep neural networks (DNNs) has recently attracted a great deal of attention.
1 code implementation • 13 Dec 2021 • Ziwei Yu, Linlin Yang, Shicheng Chen, Angela Yao
This paper addresses the 3D point cloud reconstruction and 3D pose estimation of the human hand from a single RGB image.
no code implementations • ICLR 2022 • Kerui Gu, Linlin Yang, Angela Yao
We do a deep dive on the inference and back-propagation of integral pose regression to better understand the causes behind the performance and training differences.
no code implementations • ICCV 2021 • Kerui Gu, Linlin Yang, Angela Yao
Heatmap-based detection methods are dominant for 2D human pose estimation even though regression is more intuitive.
Ranked #5 on
Pose Estimation
on COCO val2017
no code implementations • ICCV 2021 • Linlin Yang, Shicheng Chen, Angela Yao
By design, we introduce data augmentation of differing difficulties, consistency regularizer, label correction and sample selection for RGB-based 3D hand pose estimation.
no code implementations • 25 Jul 2020 • Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, Radu Timofte
To the best of our knowledge, this work is the first systematic review on VSR tasks, and it is expected to make a contribution to the development of recent studies in this area and potentially deepen our understanding to the VSR techniques based on deep learning.
no code implementations • CVPR 2020 • Li'an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David Doermann, Guodong Guo, Rongrong Ji
Conventional learning methods simplify the bilinear model by regarding two intrinsically coupled factors independently, which degrades the optimization procedure.
no code implementations • 30 Apr 2020 • Li'an Zhuo, Baochang Zhang, Hanlin Chen, Linlin Yang, Chen Chen, Yanjun Zhu, David Doermann
To this end, a Child-Parent (CP) model is introduced to a differentiable NAS to search the binarized architecture (Child) under the supervision of a full-precision model (Parent).
no code implementations • ECCV 2020 • Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek, Shreyas Hampali, Mahdi Rad, Zhaohui Zhang, Shipeng Xie, Mingxiu Chen, Boshen Zhang, Fu Xiong, Yang Xiao, Zhiguo Cao, Junsong Yuan, Pengfei Ren, Weiting Huang, Haifeng Sun, Marek Hrúz, Jakub Kanis, Zdeněk Krňoul, Qingfu Wan, Shile Li, Linlin Yang, Dongheui Lee, Angela Yao, Weiguo Zhou, Sijia Mei, Yun-hui Liu, Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Philippe Weinzaepfel, Romain Brégier, Grégory Rogez, Vincent Lepetit, Tae-Kyun Kim
To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.
no code implementations • ICCV 2019 • Linlin Yang, Shile Li, Dongheui Lee, Angela Yao
Hand pose estimation from monocular RGB inputs is a highly challenging task.
no code implementations • CVPR 2019 • Linlin Yang, Angela Yao
Hand image synthesis and pose estimation from RGB images are both highly challenging tasks due to the large discrepancy between factors of variation ranging from image background content to camera viewpoint.