35 citations · 173 across the 29 of their papers we have counts for
29 papers
Towards more realistic human motion prediction with attention to motion coordination
Pengxiang Ding, Jianqin Yin
Joint relation modeling is a curial component in human motion prediction. Most existing methods rely on skeletal-based graphs to build the joint relations, where local interactive…
SiT-MLP: A Simple MLP with Point-wise Topology Feature Learning for Skeleton-based Action Recognition
Shaojie Zhang, Jianqin Yin, Yonghao Dang +1
Graph convolution networks (GCNs) have achieved remarkable performance in skeleton-based action recognition. However, previous GCN-based methods rely on elaborate human priors exce…
Target-Aware Spatio-Temporal Reasoning via Answering Questions in Dynamics Audio-Visual Scenarios
Yuanyuan Jiang, Jianqin Yin
Audio-visual question answering (AVQA) is a challenging task that requires multistep spatio-temporal reasoning over multimodal contexts. Recent works rely on elaborate target-agnos…
MLP-AIR: An Efficient MLP-Based Method for Actor Interaction Relation Learning in Group Activity Recognition
Guoliang Xu, Jianqin Yin
The task of Group Activity Recognition (GAR) aims to predict the activity category of the group by learning the actor spatial-temporal interaction relation in the group. Therefore,…
SDVRF: Sparse-to-Dense Voxel Region Fusion for Multi-modal 3D Object Detection
Binglu Ren, Jianqin Yin
In the perception task of autonomous driving, multi-modal methods have become a trend due to the complementary characteristics of LiDAR point clouds and image data. However, the pe…
Global Relation Modeling and Refinement for Bottom-Up Human Pose Estimation
Ruoqi Yin, Jianqin Yin
In this paper, we concern on the bottom-up paradigm in multi-person pose estimation (MPPE). Most previous bottom-up methods try to consider the relation of instances to identify di…
An Improved Baseline Framework for Pose Estimation Challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop
Jiajun Fu, Yonghao Dang, Ruoqi Yin +4
This technical report describes our first-place solution to the pose estimation challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop. In this chal…
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows
Chao Qi, Jianqin Yin, Jinghang Xu +1
This work introduces a new task of instance-incremental scene graph generation: Given a scene of the point cloud, representing it as a graph and automatically increasing novel inst…
An end-to-end multi-scale network for action prediction in videos
Xiaofa Liu, Jianqin Yin, Yuan Sun +2
In this paper, we develop an efficient multi-scale network to predict action classes in partial videos in an end-to-end manner. Unlike most existing methods with offline feature ge…
Leveraging the Video-level Semantic Consistency of Event for Audio-visual Event Localization
Yuanyuan Jiang, Jianqin Yin, Yonghao Dang
Audio-visual event (AVE) localization has attracted much attention in recent years. Most existing methods are often limited to independently encoding and classifying each video seg…
Kinematics Modeling Network for Video-based Human Pose Estimation
Yonghao Dang, Jianqin Yin, Shaojie Zhang +2
Estimating human poses from videos is critical in human-computer interaction. Joints cooperate rather than move independently during human movement. There are both spatial and temp…
Past and Future Motion Guided Network for Audio Visual Event Localization
Tingxiu Chen, Jianqin Yin, Jin Tang
In recent years, audio-visual event localization has attracted much attention. It's purpose is to detect the segment containing audio-visual events and recognize the event category…
Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention
Wei Dai, Rui Liu, Tianyi Wu +3
Accurate and unbiased examinations of skin lesions are critical for the early diagnosis and treatment of skin diseases. Visual features of skin lesions vary significantly because t…
Learning Constrained Dynamic Correlations in Spatiotemporal Graphs for Motion Prediction
Jiajun Fu, Fuxing Yang, Yonghao Dang +2
Human motion prediction is challenging due to the complex spatiotemporal feature modeling. Among all methods, graph convolution networks (GCNs) are extensively utilized because of…
Rich Action-semantic Consistent Knowledge for Early Action Prediction
Xiaoli Liu, Jianqin Yin, Di Guo +1
Early action prediction (EAP) aims to recognize human actions from a part of action execution in ongoing videos, which is an important task for many practical applications. Most pr…
Real-World Semantic Grasp Detection Based on Attention Mechanism
Mingshuai Dong, Shimin Wei, Jianqin Yin +1
Recognizing the category of the object and using the features of the object itself to predict grasp configuration is of great significance to improve the accuracy of the grasp dete…
Amodal segmentation just like doing a jigsaw
Xunli Zeng, Jianqin Yin
Amodal segmentation is a new direction of instance segmentation while considering the segmentation of the visible and occluded parts of the instance. The existing state-of-the-art…
Uncertainty-aware Human Motion Prediction
Pengxiang Ding, Jianqin Yin
Human motion prediction is essential for tasks such as human motion analysis and human-robot interactions. Most existing approaches have been proposed to realize motion prediction.…
Relation-Based Associative Joint Location for Human Pose Estimation in Videos
Yonghao Dang, Jianqin Yin, Shaojie Zhang
Video-based human pose estimation (VHPE) is a vital yet challenging task. While deep learning methods have made significant progress for the VHPE, most approaches to this task impl…
An Attractor-Guided Neural Networks for Skeleton-Based Human Motion Prediction
Pengxiang Ding, Junying Wang, Jianqin Yin
Joint relation modeling is a curial component in human motion prediction. Most existing methods tend to design skeletal-based graphs to build the relations among joints, where loca…
Temporal Consistency Two-Stream CNN for Human Motion Prediction
Jin Tang, Jin Zhang, Jianqin Yin
Fusion is critical for a two-stream network. In this paper, we propose a novel temporal fusion (TF) module to fuse the two-stream joints' information to predict human motion, inclu…
Mask-GD Segmentation Based Robotic Grasp Detection
Mingshuai Dong, Shimin Wei, Xiuli Yu +1
The reliability of grasp detection for target objects in complex scenes is a challenging task and a critical problem that needs to be solved urgently in practical application. At p…
Multi-grained Trajectory Graph Convolutional Networks for Habit-unrelated Human Motion Prediction
Jin Liu, Jianqin Yin
Human motion prediction is an essential part for human-robot collaboration. Unlike most of the existing methods mainly focusing on improving the effectiveness of spatiotemporal mod…
SDMTL: Semi-Decoupled Multi-grained Trajectory Learning for 3D human motion prediction
Xiaoli Liu, Jianqin Yin
Predicting future human motion is critical for intelligent robots to interact with humans in the real world, and human motion has the nature of multi-granularity. However, most of…