33 citations · 88 across the 9 of their papers we have counts for
9 papers
Learning Hierarchical Graph Neural Networks for Image Clustering
Yifan Xing, Tong He, Tianjun Xiao +6
We propose a hierarchical graph neural network (GNN) model that learns how to cluster a set of images into an unknown number of identities using a training set of images annotated…
Semi-TCL: Semi-Supervised Track Contrastive Representation Learning
Wei Li, Yuanjun Xiong, Shuo Yang +3
Online tracking of multiple objects in videos requires strong capacity of modeling and matching object appearances. Previous methods for learning appearance embedding mostly rely o…
MTAG: Modal-Temporal Attention Graph for Unaligned Human Multimodal Language Sequences
Jianing Yang, Yongxin Wang, Ruitao Yi +5
Human communication is multimodal in nature; it is through multiple modalities such as language, voice, and facial expressions, that opinions and emotions are expressed. Data in th…
Graph Neural Networks for 3D Multi-Object Tracking
Xinshuo Weng, Yongxin Wang, Yunze Man +1
3D Multi-object tracking (MOT) is crucial to autonomous systems. Recent work often uses a tracking-by-detection pipeline, where the feature of each object is extracted independentl…
What Gives the Answer Away? Question Answering Bias Analysis on Video QA Datasets
Jianing Yang, Yuying Zhu, Yongxin Wang +3
Question answering biases in video QA datasets can mislead multimodal model to overfit to QA artifacts and jeopardize the model's ability to generalize. Understanding how strong th…
GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning
Xinshuo Weng, Yongxin Wang, Yunze Man +1
3D Multi-object tracking (MOT) is crucial to autonomous systems. Recent work uses a standard tracking-by-detection pipeline, where feature extraction is first performed independent…
Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
Yongxin Wang, Kris Kitani, Xinshuo Weng
Object detection and data association are critical components in multi-object tracking (MOT) systems. Despite the fact that the two components are dependent on each other, prior wo…
Detecting Attended Visual Targets in Video
Eunji Chong, Yongxin Wang, Nataniel Ruiz +1
We address the problem of detecting attention targets in video. Our goal is to identify where each person in each frame of a video is looking, and correctly handle the case where t…
Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency
Eunji Chong, Nataniel Ruiz, Yongxin Wang +3
This paper addresses the challenging problem of estimating the general visual attention of people in images. Our proposed method is designed to work across multiple naturalistic so…