Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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書(shū)目名稱Computer Vision – ECCV 2022影響因子(影響力)




書(shū)目名稱Computer Vision – ECCV 2022影響因子(影響力)學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2022網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Computer Vision – ECCV 2022網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2022被引頻次




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書(shū)目名稱Computer Vision – ECCV 2022年度引用




書(shū)目名稱Computer Vision – ECCV 2022年度引用學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2022讀者反饋




書(shū)目名稱Computer Vision – ECCV 2022讀者反饋學(xué)科排名

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,Designing One Unified Framework for?High-Fidelity Face Reenactment and?Swapping,and practical-unfriendly. In this paper, we propose an effective end-to-end unified framework to achieve both tasks. Unlike existing methods that directly utilize pre-estimated structures and do not fully exploit their potential similarity, our model sufficiently transfers identity and attribute bas

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,Sobolev Training for?Implicit Neural Representations with?Approximated Image Derivatives, kinds of signals due to its continuous, differentiable properties, showing superiorities to classical discretized representations. However, the training of neural networks for INRs only utilizes input-output pairs, and the derivatives of the target output with respect to the input, which can be acc

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Deep Bayesian Video Frame Interpolation,part. Our approach learns posterior distributions of optical flows and frames to be interpolated, which is optimized via learned gradient descent for fast convergence. Each learned step is a lightweight network manipulating gradients of the log-likelihood of estimated frames and flows. Such gradient

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,Cross Attention Based Style Distribution for?Controllable Person Image Synthesis,e propose a cross attention based style distribution module that computes between the source semantic styles and target pose for pose transfer. The module intentionally selects the style represented by each semantic and distributes them according to the target pose. The attention matrix in cross att