Computer Vision – ACCV 2020
Springer International Publishing (Verlag)
978-3-030-69537-8 (ISBN)
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 visionPart 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.
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.- 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.
| Erscheinungsdatum | 01.03.2021 |
|---|---|
| Reihe/Serie | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Lecture Notes in Computer Science |
| Zusatzinfo | XVIII, 715 p. 284 illus., 278 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1110 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Applications • Artificial Intelligence • biomedical image analysis • Computer Networks • Computer Science • computer vision • conference proceedings • Image Analysis • Image Processing • Image Quality • image reconstruction • Image Segmentation • Imaging Systems • Informatics • machine learning • Network Protocols • Neural networks • pattern recognition • Research • Signal Processing |
| ISBN-10 | 3-030-69537-9 / 3030695379 |
| ISBN-13 | 978-3-030-69537-8 / 9783030695378 |
| Zustand | Neuware |
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