Pattern Recognition and Computer Vision: 4th Chinese Conference, PRCV 2021, Beijing, China, October 29 November 1, 2021, Proceedings, Part IV [Paperback]

The 4-volume set LNCS 13019, 13020, 13021 and 13022 constitutes the refereed proceedings of the 4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021.

The 201 full papers presented were carefully reviewed and selected from 513 submissions. The papers have been organized in the following topical sections: Object Detection, Tracking and Recognition; Computer Vision, Theories and Applications, Multimedia Processing and Analysis; Low-level Vision and Image Processing; Biomedical Image Processing and Analysis; Machine Learning, Neural Network and Deep Learning, and New Advances in Visual Perception and Understanding.

Machine Learning, Neural Network and Deep Learning.- Edge-Wise One-Level Global Pruning on NAS generated networks.- Convolution Tells Where to Look.- Robust Single-step Adversarial Training with Regularizer.- Texture-guided U-Net for OCT-to-OCTA Generation.- Learning Key Actors and Their Interactions for Group Activity Recognition.- Attributed Non-negative Matrix Multi-Factorization for Data Representation.- Improved Categorical Cross-Entropy Loss for Training Deep Neural Networks with Noisy Labels.- A Residual Correction Approach for Semi-supervised Semantic Segmentation.- Hypergraph Convolutional Network with Hybrid Higher-order Neighbors.- Text-Aware Single Image Specular Highlight Removal.- Minimizing Wasserstein-1 Distance by Quantile Regression for GANs Model.- A Competition of Shape and Texture Bias by Multi-View Image Representation.- Learning Indistinguishable and Transferable Adversarial Examples.- Efficient Object Detection and Classification of Ground Objects fromThermal Infrared Remote Sensing Image Based on Deep Learning.- MEMA-NAS: Memory-Efficient Multi-Agent Neural Architecture Search.- Adversarial Decoupling for Weakly Supervised Semantic Segmentation.- Towards End-to-End Embroidery Stylló%