32 Result(s)
within
Conference Paper
Han**g Wang
English
Computer Imaging, Vision, Pattern Recognition and Graphics
-
Chapter and Conference Paper
OctPCGC-Net: Learning Octree-Structured Context Entropy Model for Point Cloud Geometry Compression
In Point Cloud Geometry Compression (PCGC), an accurate context entropy model is necessary to reduce spatial redundancy. The octree-based auto-regressive context entropy model has great potential to explore la...
-
Chapter and Conference Paper
An Effective Dynamic Reweighting Method for Unbiased Scene Graph Generation
Despite the remarkable advancements in Scene Graph Generation (SGG) in recent years, the precise capture and modeling of long-tail object relationships remain persistent challenges in the field. Conventional m...
-
Chapter and Conference Paper
Spatio-Temporal Self-supervision for Few-Shot Action Recognition
Few-shot action recognition aims to classify unseen action classes with limited labeled training samples. Most current works follow the metric learning technology to learn a good embedding and an appropriate c...
-
Chapter and Conference Paper
Cascaded-Scoring Tracklet Matching for Multi-object Tracking
Multi-object tracking (MOT) aims at locating the object of interest in a successive video sequence and associating the same moving object frame by frame. Most existing approaches to MOT lack the integration of...
-
Chapter and Conference Paper
Joint Relation Modeling and Feature Learning for Class-Incremental Facial Expression Recognition
Due to the diversity of human emotions, it is often difficult to collect all the expression categories at once in many practical applications. In this paper, we investigate facial expression recognition (FER) ...
-
Chapter and Conference Paper
An Effective Visible-Infrared Person Re-identification Network Based on Second-Order Attention and Mixed Intermediate Modality
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Due to the significant cross-modality discrepancy, it is difficult to learn discriminative feat...
-
Chapter and Conference Paper
UAM-Net: An Attention-Based Multi-level Feature Fusion UNet for Remote Sensing Image Segmentation
Semantic segmentation of Remote Sensing Images (RSIs) is an essential application for precision agriculture, environmental protection, and economic assessment. While UNet-based networks have made significant p...
-
Chapter and Conference Paper
MCKIE: Multi-class Key Information Extraction from Complex Documents Based on Graph Convolutional Network
The majority of key information extraction in document analysis work relies on simple layout scenes with few classes, such as the date and amount on invoices or receipts. However, many document applications en...
-
Chapter and Conference Paper
GridIIS: Grid Based Interactive Image Segmentation
Interactive segmentation enables users to specify the object of interest (OOI) via various interaction strategies to obtain accurate segmentation results. An ideal interactive method should efficiently and acc...
-
Chapter and Conference Paper
Pseudo Labels Refinement with Stable Cluster Reconstruction for Unsupervised Re-identification
Most existing unsupervised re-identification uses a clustering-based approach to generate pseudo-labels as supervised signals, allowing deep neural networks to learn discriminative representations without anno...
-
Chapter and Conference Paper
DeCAB: Debiased Semi-supervised Learning for Imbalanced Open-Set Data
Semi-supervised learning (SSL) has received significant attention due to its ability to use limited labeled data and various unlabeled data to train models with high generalization performance. However, the as...
-
Chapter and Conference Paper
Frequency and Spatial Domain Filter Network for Visual Object Tracking
Cross-correlation serves as the core similarity calculation operation in Siamese-based trackers, and generally produces response maps with high values at the target center. During this process, global context,...
-
Chapter and Conference Paper
LLM Collaboration PLM Improves Critical Information Extraction Tasks in Medical Articles
With the development of modern medical informatics and databases, medical professionals are increasingly inclined to use evidence-based medicine to guide their learning and work. Evidence-based medicine requir...
-
Chapter and Conference Paper
A Bibliographic Study of Macular Fovea Detection: AI-Based Methods, Applications, and Issues
This study utilized a method of bibliographic analysis and text mining on the literature from databases of Web of Science (WOS) and Scopus. About 79 and 632 related articles are collected from WOS and Scopus, ...
-
Chapter and Conference Paper
Real-Time Train Rescheduling with Passenger Demand for Rolling Stock Rescue
With the expansion of urban rail transit systems, there are more and more equipment failures, especially train failures, which could result in serious disruptions on the operation of trains. Hence, the effecti...
-
Chapter and Conference Paper
Ocular Tactile Vibration Intervention in VR and Its Modeling Coupled with Visual Fusion
The main application of virtual reality (VR) is to immerse users in the three-dimensional simulation environment and experience the virtual reality world. At present, VR products and content on the market have...
-
Chapter and Conference Paper
Study on the Evaluation Method of the Clarity of Critical Areas of Digital Images
In response to the current needs of machine vision systems for digital image clarity evaluation methods, this paper proposes a scientific and objective image critical area clarity evaluation method, focusing o...
-
Chapter and Conference Paper
Semantic-Aware Non-local Network for Handwritten Mathematical Expression Recognition
Handwritten mathematical expression recognition (HMER) is a challenging task due to its complex two-dimensional structure of mathematical expressions and the high similarity between handwritten texts. Most exi...
-
Chapter and Conference Paper
A Feature Extraction Algorithm for Enhancing Graphical Local Adaptive Threshold
In order to solve the problem that the ORB algorithm increases the probability of feature point loss and mis-matching in some cases such as insufficient light intensity, low texture, large camera rotation, etc...
-
Chapter and Conference Paper
Joint Pixel-Level and Feature-Level Unsupervised Domain Adaptation for Surveillance Face Recognition
Face recognition (FR) is one of the most successful image analysis and understanding applications, which has recently received significant attentions. However, despite the remarkable progress in face recogniti...
