Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29 - November 1, 2021, Proceedings, Part III

Low-level Vision and Image Processing.- SaliencyBERT: Recurrent Attention Network for Target-oriented Multimodal Sentiment Classification.- Latency-Constrained Spatial-Temporal Aggregated Architecture Search for Video Deraining.- Semantic-Driven Context Aggregation Network for Underwater Image Enhancement.- A Multi-resolution Medical Image Fusion Network with Iterative Back-Projection.- Multi-Level Discriminator and Wavelet Loss for Image Inpainting with Large Missing Area.- 3D 2Unet: 3D Deformable Unet for Low-Light Video Enhancement.- Single Image Specular Highlight Removal on Natural Scenes.- Document image binarization using visibility detection and point cloud segmentation.- LF-MAGNet: Learning Mutual Attention Guidance of Sub-Aperture Images for Light Field Image Super-Resolution.- Infrared Small Target Detection Based on Weighted Variation Coefficient Local Contrast Measure.- Scale-aware Distillation Network for Lightweight Image Super-Resolution.- Deep Multi-Illumination Fusion for Low-Light Image Enhancement.- Relational Attention with Textual Enhanced Transformer For Image Captioning.- Non-local Network Routing for Perceptual Image Super-Resolution.- Multi-Focus Image Fusion with Cooperative Image Multiscale Decomposition.- An Enhanced Multi-Frequency Learned Image Compression Method.- Noise Map Guided Inpainting Network for Low-Light Image Enhancement.- FIE-GAN: Illumination Enhancement Network for Face Recognition.- Illumination-Aware Image Quality Assessment for Enhanced Low-light Image.- Smooth Coupled Tucker Decomposition for Hyperspectral Image Super-resolution.- Self-Supervised Video Super-Resolution by Spatial Constraint and Temporal Fusion.- ODE-Inspired Image Denoiser: An End-to-End Dynamical Denoising Network.- Image Outpainting with Depth Assistance.- Light-weight Multi-channel Aggregation Network for Image Super-resolution.- Slow Video Detection Based on Spatial-temporal Feature Representation.- Biomedical Image Processing and Analysis.- The NL-SC Net for Skin Lesion Segmentation.- Two-Stage COVID-19 Lung Segmentation from CT Images by Integrating Rib Outlining and Contour Refinement.- Deep Semantic Edge for Cell Counting and Localization in Time-Lapse Microscopy Images.- A Guided Attention 4D Convolutional Neural Network for Modeling Spatio-Temporal Patterns of Functional Brain Networks.- Tiny-FASNet: A Tiny Face Anti-spoofing Method Based on Tiny Module.- Attention-based Node-Edge Graph Convolutional Networks for Identification of Autism Spectrum Disorder Using Multi-Modal MRI Data.- Segmentation of Intracellular Structures in Fluorescence Microscopy Images by Fusing Low-Level Feature.- Interactive Attention Sampling Network for Clinical Skin Disease Image Classification.- Cross-Model Attention Method for Medical Image Enhancement.- Multi-modal Face Anti-Spoofing based on a Single Image.- Non-Significant information Enhancement based Attention Network for Face Anti-Spoofing.- Early Diagnosis of Alzheimer's Disease Using 3D Residual Attention Network Based on Hippocampal Multi-indices Feature Fusion.- HPCReg-Net: Unsupervised U-Net Integrating Dilated Convolution and Residual Attention for Hippocampus Registration.- Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis.- Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction.- Model-based gait recognition using graph network with pose sequences.- Multi-directional Attention Network for Segmentation of Pediatric Echocardiographic.- Deep-based Super-angular Resolution for Diffusion Imaging.- A Multiple Scale Encoders Network for Stroke Lesion Segmentation.- Nodule Synthesis and Selection for Augmenting Chest X-ray Nodule Detection.- Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation.- DPACN: Dual Prior-guided Astrous Convolutional Network for Adhesive Pulmonary Nodules Segmentation on CT Sequence.- Face A