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Computer Vision – ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020, Proceedings, Part V de Adrien Bartoli

Computer Vision – ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020, Proceedings, Part V: Lecture Notes in Computer Science, cartea 12539

Editat de Adrien Bartoli, Andrea Fusiello
en Limba Engleză Paperback – 31 ian 2021
The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic.
The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics.

Part V includes: The 16th Embedded Vision Workshop; Real-World Computer Vision from Inputs with Limited Quality (RLQ); The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS 2020); The Visual Object Tracking Challenge Workshop (VOT 2020); and Video Turing Test: Toward Human-Level Video Story Understanding. 

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Specificații

ISBN-13: 9783030682378
ISBN-10: 3030682374
Pagini: 752
Ilustrații: XXVIII, 752 p. 298 illus., 283 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.08 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Image Processing, Computer Vision, Pattern Recognition, and Graphics

Locul publicării:Cham, Switzerland

Cuprins

W27 - The 16th Embedded Vision Workshop.- Hardware Architecture of Embedded Inference Accelerator and Analysis of Algorithms for Depthwise and Large-Kernel Convolutions.- SegBlocks: Towards Block-Based Adaptive Resolution Networks for Fast Segmentation.- Weight-dependent Gates for Differentiable Neural Network Pruning.- QuantNet: Learning to Quantize by Learning within Fully Differentiable Framework.- An Efficient Method for Face Quality Assessment on the Edge.- Efficient Approximation of Filters for High-Accuracy Binary Convolutional Neural Networks.- One Weight Bitwidth to Rule Them All.- Real-time detection of multiple targets from a moving 360 panoramic imager in the wild.- Post Training Mixed-precision Quantization based on Key Layers Selection.- Subtensor Quantization for Mobilenets.- Feed-Forward On-Edge Fine-Tuning Using Static Synthetic Gradient Modules.- W29 - Real-World Computer Vision from Inputs with Limited Quality (RLQ).- Reinforcement Learning for Improving Object Detection.- Collaborative Learning with Pseudo Labels for Robust Classification in the Presence of Noisy Labels.- Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training.- What Does CNN Shift Invariance Look Like? A Visualization Study.- Challenges from Fast Camera Motion and Image Blur: Dataset and Evaluation.- Self-Supervised Attribute-Aware Re nement Network for Low-Quality Text Recognition.- Face Mask Invariant End-to-End Face Recognition.- Visible Feature Guidance for Crowd Pedestrian Detection.- The Impact of Real Rain in a Vision Task.- Hard Occlusions in Visual Object Tracking.- The 1st Tiny Object Detection Challenge: Methods and Results.- Effective Feature Enhancement and Model Ensemble Strategies in Tiny Object Detection.- Exploring Effective Methods to Improve the Performance of Tiny Object Detection.- UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results.- A Dual Residual Network with Channel Attentionfor Image Restoration.- Transform Domain Pyramidal Dilated Convolution Networks For Restoration of Under Display Camera Images.- Deep Atrous Guided Filter for Image Restoration in Under Display Cameras.- Residual and Dense UNet for Under-display Camera Restoration.- W31 - The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS 2020).- Body Shape Privacy in Images: Understanding Privacy and Preventing Automatic Shape Extraction.- Adversarial Training against Location-Optimized Adversarial Patches.- Revisiting the Threat Space for Vision-based Keystroke Inference Attacks.- Black-Box Face Recovery from Identity Features.- Privacy-Aware Face Recognition with Lensless Multi-Pinhole Camera.- Frequency-Tuned Universal Adversarial Perturbations.- Face-Image Source Generator Identification.- Spatio-Temporal Handwriting Imitation.- W32 - The Visual Object Tracking Challenge Workshop VOT2020.- The Eighth Visual Object Tracking VOT2020 ChallengeResults.- Robust Long-Term Object Tracking via Improved Discriminative Model Prediction.- An  Exploration of Target-Conditioned Segmentation Methods for Visual Object Trackers.- AF2S: An Anchor-Free Two-Stage Tracker Based on a Strong SiamFC Baseline.- RPT: Learning Point Set Representation for Siamese Visual Tracking.- AFOD: Adaptive Focused Discriminative Segmentation Tracker.- Cascaded Tracking via Pyramid Dense Capsules.- W33 - Video Turing Test: Toward Human-Level Video Story Understanding.- GCF-Net: Gated Clip Fusion Network for Video Action Recognition.- Late Temporal Modeling in 3D CNNs with BERT.