no code implementations • 2 Jul 2023 • Zhenhua Wang, Kaining Ying, Jiajun Meng, Jifeng Ning
First, based on the popular AVA dataset created for action detection, we establish a new HID benchmark, termed AVA-Interaction (AVA-I), by adding annotations on interactive relations in a frame-by-frame manner.
1 code implementation • 21 Mar 2023 • Yongkang Cheng, Shaoli Huang, Jifeng Ning, Ying Shan
This paper presents a novel approach for estimating human body shape and pose from monocular images that effectively addresses the challenges of occlusions and depth ambiguity.
Ranked #18 on 3D Human Pose Estimation on 3DPW
no code implementations • ICCV 2023 • Dan Liu, Jin Hou, Shaoli Huang, Jing Liu, Yuxin He, Bochuan Zheng, Jifeng Ning, Jingdong Zhang
To break the deadlock, we present LoTE-Animal, a large-scale endangered animal dataset collected over 12 years, to foster the application of deep learning in rare species conservation.
1 code implementation • CVPR 2022 • Peng Du, Jifeng Ning, Jiguang Cui, Shaoli Huang, Xinchao Wang, Jiaxin Wang
Further, an optimized GES energy term is presented to reasonably determine the weights of the sampling points on the geometric structure, and the term is added into the Global Similarity Prior (GSP) stitching model called GES-GSP to achieve a smooth transition between local alignment and geometric structure preservation.
no code implementations • 30 May 2020 • Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Instead of traditional bandwise total variation, we use the SSTV regularization to simultaneously consider global spatial structure and spectral correlation of neighboring bands.
no code implementations • 28 May 2020 • Haijin Zeng, Xiaozhen Xie, Jifeng Ning
Higher-order low-rank tensor arises in many data processing applications and has attracted great interests.
no code implementations • 8 May 2020 • Haijin Zeng, Xiaozhen Xie, Jifeng Ning
From one aspect, local LR of HSIs is formulated using a non-convex $L_{\gamma}$-norm, which provides a closer approximation to the matrix rank than the traditional NN.
no code implementations • 19 Apr 2020 • Haijin Zeng, Xiaozhen Xie, Jifeng Ning
In this paper, we propose a novel model to recover a low-rank tensor by simultaneously performing double nuclear norm regularized low-rank matrix factorizations to the all-mode matricizations of the underlying tensor.
no code implementations • CVPR 2016 • Jifeng Ning, Jimei Yang, Shaojie Jiang, Lei Zhang, Ming-Hsuan Yang
Structured support vector machine (SSVM) based methods has demonstrated encouraging performance in recent object tracking benchmarks.