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[null,null,"Titolo",null,"Computer Vision – ACCV 2020 [[electronic resource] ] : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 – December 4, 2020, Revised Selected Papers, Part IV / / edited by Hiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021"]
[null,null,"ISBN",null,"3-030-69538-7"]
[null,null,"Edizione",null,"[1st ed. 2021.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVIII, 715 p. 284 illus., 278 illus. in color.)"]
[null,null,"Collana",null,"Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 12625"]
[null,null,"Disciplina",null,"006.37"]
[null,null,"Soggetti",null,"Computer vision"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Deep Learning for Computer Vision -- In-sample Contrastive Learning and Consistent Attention for Weakly Supervised Object Localization -- Exploiting Transferable Knowledge for Fairness-aware Image Classification -- Introspective Learning by Distilling Knowledge from Online Self-explanation -- Hyperparameter-Free Out-of-Distribution Detection Using Cosine Similarity -- Meta-Learning with Context-Agnostic Initialisations -- Second Order enhanced Multi-glimpse Attention in Visual Question Answering -- Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection -- Unified Density-Aware Image Dehazing and Object Detection in Real-World Hazy Scenes -- Part-aware Attention Network for Person Re-Identification -- Image Captioning through Image Transformer -- "]
[{"$nulls":4},"Feature Variance Ratio-Guided Channel Pruning for Deep Convolutional Network Acceleration -- Learn more, forget less: Cues from human brain -- Knowledge Transfer Graph for Deep Collaborative Learning -- Regularizing Meta-Learning via Gradient Dropout -- Vax-a-Net: Training-time Defence Against Adversarial Patch Attacks -- Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed -- Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation -- Double Targeted Universal Adversarial Perturbations -- Adversarially Robust Deep Image Super-Resolution using Entropy Regularization -- Online Knowledge Distillation via Multi-branch Diversity Enhancement -- Rotation Equivariant Orientation Estimation for Omnidirectional Localization -- Contextual Semantic Interpretability -- Few-Shot Object Detection by Second-order Pooling -- Depth-Adapted CNN for RGB-D cameras -- Generative Models for Computer Vision -- Over-exposure Correction via Exposure and Scene Information Disentanglement -- Novel-View Human Action Synthesis -- Augmentation Network for Generalised Zero-Shot Learning -- Local Facial Makeup Transfer via Disentangled Representation -- OpenGAN: Open Set Generative Adversarial Networks -- CPTNet: Cascade Pose Transform Network for Single Image Talking Head Animation -- TinyGAN: Distilling BigGAN for Conditional Image Generation -- A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-tuning their class-embeddings -- RF-GAN: A Light and Reconfigurable Network for Unpaired Image-to-Image Translation -- GAN-based Noise Model for Denoising Real Images -- Emotional Landscape Image Generation Using Generative Adversarial Networks -- Feedback Recurrent Autoencoder for Video Compression -- MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network -- DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution -- dpVAEs: Fixing Sample Generation for Regularized VAEs -- MagGAN: High-Resolution Face Attribute Editing with Mask-Guided Generative Adversarial Network -- EvolGAN: Evolutionary Generative Adversarial Networks -- Sequential View Synthesis with Transformer."]
[null,null,null,"Sommario/riassunto","The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually."]