85 citations · 167 across the 21 of their papers we have counts for
21 papers
Exploiting Aggregation and Segregation of Representations for Domain Adaptive Human Pose Estimation
Qucheng Peng, Ce Zheng, Zhengming Ding +2
Human pose estimation (HPE) has received increasing attention recently due to its wide application in motion analysis, virtual reality, healthcare, etc. However, it suffers from th…
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed Transformer
Wenhan Wu, Ce Zheng, Zihao Yang +3
Recently, transformers have demonstrated great potential for modeling long-term dependencies from skeleton sequences and thereby gained ever-increasing attention in skeleton action…
Multi-View Attentive Contextualization for Multi-View 3D Object Detection
Xianpeng Liu, Ce Zheng, Ming Qian +5
We present Multi-View Attentive Contextualization (MvACon), a simple yet effective method for improving 2D-to-3D feature lifting in query-based multi-view 3D (MV3D) object detectio…
SignLLM: Sign Language Production Large Language Models
Sen Fang, Chen Chen, Lei Wang +3
In this paper, we propose SignLLM, a multilingual Sign Language Production (SLP) large language model, which includes two novel multilingual SLP modes MLSF and Prompt2LangGloss tha…
A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation
Qucheng Peng, Ce Zheng, Chen Chen
3D human pose data collected in controlled laboratory settings present challenges for pose estimators that generalize across diverse scenarios. To address this, domain generalizati…
A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation
Qitao Zhao, Ce Zheng, Mengyuan Liu +1
The dominant paradigm in 3D human pose estimation that lifts a 2D pose sequence to 3D heavily relies on long-term temporal clues (i.e., using a daunting number of video frames) for…
Source-free Domain Adaptive Human Pose Estimation
Qucheng Peng, Ce Zheng, Chen Chen
Human Pose Estimation (HPE) is widely used in various fields, including motion analysis, healthcare, and virtual reality. However, the great expenses of labeled real-world datasets…
LAMP: Leveraging Language Prompts for Multi-person Pose Estimation
Shengnan Hu, Ce Zheng, Zixiang Zhou +2
Human-centric visual understanding is an important desideratum for effective human-robot interaction. In order to navigate crowded public places, social robots must be able to inte…
Part Aware Contrastive Learning for Self-Supervised Action Recognition
Yilei Hua, Wenhan Wu, Ce Zheng +4
In recent years, remarkable results have been achieved in self-supervised action recognition using skeleton sequences with contrastive learning. It has been observed that the seman…
Annotation-efficient learning for OCT segmentation
Haoran Zhang, Jianlong Yang, Ce Zheng +2
Deep learning has been successfully applied to OCT segmentation. However, for data from different manufacturers and imaging protocols, and for different regions of interest (ROIs),…
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver
Xianpeng Liu, Ce Zheng, Kelvin Cheng +3
The main challenge of monocular 3D object detection is the accurate localization of 3D center. Motivated by a new and strong observation that this challenge can be remedied by a 3D…
PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation
Qitao Zhao, Ce Zheng, Mengyuan Liu +2
Recently, transformer-based methods have gained significant success in sequential 2D-to-3D lifting human pose estimation. As a pioneering work, PoseFormer captures spatial relation…
POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery
Ce Zheng, Xianpeng Liu, Guo-Jun Qi +1
Transformer architectures have achieved SOTA performance on the human mesh recovery (HMR) from monocular images. However, the performance gain has come at the cost of substantial m…
DiffMesh: A Motion-aware Diffusion Framework for Human Mesh Recovery from Videos
Ce Zheng, Xianpeng Liu, Qucheng Peng +3
Human mesh recovery (HMR) provides rich human body information for various real-world applications. While image-based HMR methods have achieved impressive results, they often strug…
SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition
Wenhan Wu, Yilei Hua, Ce Zheng +3
Fully supervised skeleton-based action recognition has achieved great progress with the blooming of deep learning techniques. However, these methods require sufficient labeled data…
FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER
Ce Zheng, Matias Mendieta, Taojiannan Yang +2
Recently, vision transformers have shown great success in a set of human reconstruction tasks such as 2D human pose estimation (2D HPE), 3D human pose estimation (3D HPE), and huma…
POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognition
Ce Zheng, Matias Mendieta, Chen Chen
Facial expression recognition (FER) is an important task in computer vision, having practical applications in areas such as human-computer interaction, education, healthcare, and o…
A Lightweight Graph Transformer Network for Human Mesh Reconstruction from 2D Human Pose
Ce Zheng, Matias Mendieta, Pu Wang +2
Existing deep learning-based human mesh reconstruction approaches have a tendency to build larger networks in order to achieve higher accuracy. Computational complexity and model s…
3D Human Pose Estimation with Spatial and Temporal Transformers
Ce Zheng, Sijie Zhu, Matias Mendieta +3
Transformer architectures have become the model of choice in natural language processing and are now being introduced into computer vision tasks such as image classification, objec…
Deep Learning-Based Human Pose Estimation: A Survey
Ce Zheng, Wenhan Wu, Chen Chen +5
Human pose estimation aims to locate the human body parts and build human body representation (e.g., body skeleton) from input data such as images and videos. It has drawn increasi…
LodoNet: A Deep Neural Network with 2D Keypoint Matchingfor 3D LiDAR Odometry Estimation
Ce Zheng, Yecheng Lyu, Ming Li +1
Deep learning based LiDAR odometry (LO) estimation attracts increasing research interests in the field of autonomous driving and robotics. Existing works feed consecutive LiDAR fra…