Computer Vision - Accv 2020: 15Th Asian Conference On Computer Vision, Kyot...

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Computer Vision - Accv 2020: 15Th Asian Conference On Comput...
ISBN
9783030695378
Subject Area
Computers
Publication Name
Computer Vision - ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part IV
Publisher
Springer International Publishing A&G
Item Length
9.3 in
Subject
Hardware / General, Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Publication Year
2021
Series
Lecture Notes in Computer Science Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Cheng-Lin Liu
Item Weight
39.2 Oz
Item Width
6.1 in
Number of Pages
Xviii, 715 Pages

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030695379
ISBN-13
9783030695378
eBay Product ID (ePID)
13050397394

Product Key Features

Number of Pages
Xviii, 715 Pages
Language
English
Publication Name
Computer Vision - ACCV 2020 : 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30 - December 4, 2020, Revised Selected Papers, Part IV
Publication Year
2021
Subject
Hardware / General, Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition
Type
Textbook
Subject Area
Computers
Author
Cheng-Lin Liu
Series
Lecture Notes in Computer Science Ser.
Format
Trade Paperback

Dimensions

Item Weight
39.2 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Series Volume Number
12625
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
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.
Synopsis
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.
LC Classification Number
TA1634

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  • -***9 (61)- Feedback left by buyer.
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    Item arrived to me and was tore up from not being well packaged. Seller has still not got back to me after I messaged them about this with pictures to show how it arrived. Was supposed to be a present and now can not wrap this up and gift it. Also item was supposed to be a coloring book and it ended up being a coloring/activity book which I was not listed as such. I paid for a new item and received a wrecked item. Not pleased at all.
    Reply from: letsbeniftythrifty- Feedback replied by seller letsbeniftythrifty.- Feedback replied by seller letsbeniftythrifty.
    I did a poor job in packaging this item. Lesson learned. I issued the buyer a refund.
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    Just as described. Good packaging. FAST shipping .A+++++ debater
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    Pretty happy with the speed at which this was shipped out. Unfortunately the packaging was a bit worse for wear. Might've been bashed a bit during shipment, one of 4 sticks had a broken base and the box appeared tattered. Otherwise, item was exactly what I was after and the price not too bad.
    Reply from: letsbeniftythrifty- Feedback replied by seller letsbeniftythrifty.- Feedback replied by seller letsbeniftythrifty.
    Sorry for the damage. Glad you can still use the item. Thanks for your support!
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