43 citations · 224 across the 27 of their papers we have counts for
29 papers
GKGNet: Group K-Nearest Neighbor based Graph Convolutional Network for Multi-Label Image Recognition
Ruijie Yao, Sheng Jin, Lumin Xu +5
Multi-Label Image Recognition (MLIR) is a challenging task that aims to predict multiple object labels in a single image while modeling the complex relationships between labels and…
Aligning Bag of Regions for Open-Vocabulary Object Detection
Size Wu, Wenwei Zhang, Sheng Jin +2
Pre-trained vision-language models (VLMs) learn to align vision and language representations on large-scale datasets, where each image-text pair usually contains a bag of semantic…
ZoomNAS: Searching for Whole-body Human Pose Estimation in the Wild
Lumin Xu, Sheng Jin, Wentao Liu +4
This paper investigates the task of 2D whole-body human pose estimation, which aims to localize dense landmarks on the entire human body including body, feet, face, and hands. We p…
PoseTrans: A Simple Yet Effective Pose Transformation Augmentation for Human Pose Estimation
Wentao Jiang, Sheng Jin, Wentao Liu +3
Human pose estimation aims to accurately estimate a wide variety of human poses. However, existing datasets often follow a long-tailed distribution that unusual poses only occupy a…
3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal
Hao Meng, Sheng Jin, Wentao Liu +4
Estimating 3D interacting hand pose from a single RGB image is essential for understanding human actions. Unlike most previous works that directly predict the 3D poses of two inter…
Pose for Everything: Towards Category-Agnostic Pose Estimation
Lumin Xu, Sheng Jin, Wang Zeng +5
Existing works on 2D pose estimation mainly focus on a certain category, e.g. human, animal, and vehicle. However, there are lots of application scenarios that require detecting th…
Not All Tokens Are Equal: Human-centric Visual Analysis via Token Clustering Transformer
Wang Zeng, Sheng Jin, Wentao Liu +4
Vision transformers have achieved great successes in many computer vision tasks. Most methods generate vision tokens by splitting an image into a regular and fixed grid and treatin…
Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization
Can Wang, Sheng Jin, Yingda Guan +4
Localizing keypoints of an object is a basic visual problem. However, supervised learning of a keypoint localization network often requires a large amount of data, which is expensi…
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance
Jiachen Xu, Min Wang, Jingyu Gong +4
Prior plays an important role in providing the plausible constraint on human motion. Previous works design motion priors following a variety of paradigms under different circumstan…
Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images
Size Wu, Sheng Jin, Wentao Liu +4
This paper studies the task of estimating the 3D human poses of multiple persons from multiple calibrated camera views. Following the top-down paradigm, we decompose the task into…
Joint Depth and Normal Estimation from Real-world Time-of-flight Raw Data
Rongrong Gao, Na Fan, Changlin Li +2
We present a novel approach to joint depth and normal estimation for time-of-flight (ToF) sensors. Our model learns to predict the high-quality depth and normal maps jointly from T…
Human Pose Regression with Residual Log-likelihood Estimation
Jiefeng Li, Siyuan Bian, Ailing Zeng +4
Heatmap-based methods dominate in the field of human pose estimation by modelling the output distribution through likelihood heatmaps. In contrast, regression-based methods are mor…
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search
Lumin Xu, Yingda Guan, Sheng Jin +5
Human pose estimation has achieved significant progress in recent years. However, most of the recent methods focus on improving accuracy using complicated models and ignoring real-…
When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarks
Jiahang Wang, Sheng Jin, Wentao Liu +3
Human pose estimation is a fundamental yet challenging task in computer vision, which aims at localizing human anatomical keypoints. However, unlike human vision that is robust to…
SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation
Jianan Zhen, Qi Fang, Jiaming Sun +4
Recovering multi-person 3D poses with absolute scales from a single RGB image is a challenging problem due to the inherent depth and scale ambiguity from a single view. Addressing…
HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation
Jiefeng Li, Can Wang, Wentao Liu +2
Remarkable progress has been made in 3D human pose estimation from a monocular RGB camera. However, only a few studies explored 3D multi-person cases. In this paper, we attempt to…
Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimation
Sheng Jin, Wentao Liu, Enze Xie +4
Multi-person pose estimation is challenging because it localizes body keypoints for multiple persons simultaneously. Previous methods can be divided into two streams, i.e. top-down…
Whole-Body Human Pose Estimation in the Wild
Sheng Jin, Lumin Xu, Jin Xu +5
This paper investigates the task of 2D human whole-body pose estimation, which aims to localize dense landmarks on the entire human body including face, hands, body, and feet. As e…
3D Human Mesh Regression with Dense Correspondence
Wang Zeng, Wanli Ouyang, Ping Luo +2
Estimating 3D mesh of the human body from a single 2D image is an important task with many applications such as augmented reality and Human-Robot interaction. However, prior works…
VideoForensicsHQ: Detecting High-quality Manipulated Face Videos
Gereon Fox, Wentao Liu, Hyeongwoo Kim +3
There are concerns that new approaches to the synthesis of high quality face videos may be misused to manipulate videos with malicious intent. The research community therefore deve…
Omni-sourced Webly-supervised Learning for Video Recognition
Haodong Duan, Yue Zhao, Yuanjun Xiong +2
We introduce OmniSource, a novel framework for leveraging web data to train video recognition models. OmniSource overcomes the barriers between data formats, such as images, short…
Monocular Human Pose and Shape Reconstruction using Part Differentiable Rendering
Min Wang, Feng Qiu, Wentao Liu +3
Superior human pose and shape reconstruction from monocular images depends on removing the ambiguities caused by occlusions and shape variance. Recent works succeed in regression-b…
TRB: A Novel Triplet Representation for Understanding 2D Human Body
Haodong Duan, KwanYee Lin, Sheng Jin +3
Human pose and shape are two important components of 2D human body. However, how to efficiently represent both of them in images is still an open question. In this paper, we propos…
EgoFace: Egocentric Face Performance Capture and Videorealistic Reenactment
Mohamed Elgharib, Mallikarjun BR, Ayush Tewari +4
Face performance capture and reenactment techniques use multiple cameras and sensors, positioned at a distance from the face or mounted on heavy wearable devices. This limits their…