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|a 9783030670702
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|a Computer Vision – ECCV 2020 Workshops
|h [electronic resource] :
|b Glasgow, UK, August 23–28, 2020, Proceedings, Part III /
|c edited by Adrien Bartoli, Andrea Fusiello.
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|a 1st ed. 2020.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2020.
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|a XXVIII, 762 p. 356 illus., 338 illus. in color.
|b online resource.
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
|v 12537
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|a W24 - Advances in Image Manipulation Workshop and Challenges -- AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results -- Residual Feature Distillation Network for Lightweight Image Super-Resolution. -Efficient Image Super-Resolution using Pixel Attention -- LarvaNet: Hierarchical Super-Resolution via Multi-exit Architecture -- Efficient Super-Resolution using MobileNetV3 -- Multi-Attention Based Ultra Lightweight Image Super-Resolution -- Adaptive Hybrid Composition based Super-Resolution Network via Fine-grained Channel Pruning -- IdleSR: E cient Super-Resolution Network with Multi-Scale IdleBlocks -- IM 2020 Challenge on Learned Image Signal Processing Pipeline -- EEDNet: Enhanced Encoder Decoder Network for AutoISP -- AWNet: Attentive Wavelet Network for ImageISP -- PyNET-CA: Enhanced PyNET with Channel Attention for End-to-end Mobile Image Signal Processing -- AIM 2020 Challenge on Rendering Realistic Bokeh -- BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh -- Bokeh Rendering from Defocus Estimation -- Human Motion Transfer from Poses in the Wild -- FamilyGAN: Generating Kin Face Images using Generative Adversarial Networks -- Genetic-GAN: Synthesizing images between two domains by genetic crossover -- GIA-Net: Global Information Aware Network for Low-light Imaging -- Flexible Example-based Image Enhancement with Task Adaptive Global Feature Self-Guided Network -- A Benchmark for Burst Color Constancy -- Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration -- AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results -- Real Image Super Resolution via Heterogeneous Model Ensemble using GP-NAS -- Enhanced Adaptive Dense Connection Single Image Super-Resolution -- Self-Calibrated Attention Neural Network for Real-World Super Resolution -- FAN: Frequency Aggregation Network for Real Image Super-resolution -- Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution -- AIM 2020: Scene Relighting and Illumination Estimation Challenge -- WDRN : A Wavelet Decomposed RelightNet for Image Relighting -- SA-AE for Any-to-any Relighting -- Deep Relighting Networks for Image Light Source Manipulation -- LightNet: Deep Learning based Illumination Estimation from Virtual Images -- An Ensemble Neural Network for Scene Relighting with Light Classification -- Long-Term Human Video Generation of Multiple Futures Using Poses -- AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs -- Unconstrained Text Detection in Manga: a New Dataset and Baseline -- Joint Demosaicking and Denoising for CFA and MSFA Images using a Mosaic-Adaptive Dense Residual Network -- Gated Texture CNN for Efficient and Configurable Image Denoising -- Quantized Warping and Residual Temporal Integration for Video Super-Resolution on Fast Motions -- Pyramidal Edge-maps and Attention based Guided Thermal Super-resolution -- AIM 2020 Challenge on Image Extreme Inpainting -- Fast Light-Weight Network for Extreme Image Inpainting Challenge.
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|a 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 III includes the Advances in Image Manipulation Workshop and Challenges. .
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|a Optical data processing.
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|a Image Processing and Computer Vision.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I22021
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|a Bartoli, Adrien.
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|a Fusiello, Andrea.
|e editor.
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783030670696
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|i Printed edition:
|z 9783030670719
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
|v 12537
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|u https://doi.org/10.1007/978-3-030-67070-2
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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