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Titlebook: Computer Vision – ACCV 2022; 16th Asian Conferenc Lei Wang,Juergen Gall,Rama Chellappa Conference proceedings 2023 The Editor(s) (if applic

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樓主: frustrate
21#
發(fā)表于 2025-3-25 07:15:26 | 只看該作者
https://doi.org/10.1007/978-3-031-26348-4artificial intelligence; computer networks; computer systems; computer vision; databases; image analysis;
22#
發(fā)表于 2025-3-25 10:19:39 | 只看該作者
978-3-031-26347-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
23#
發(fā)表于 2025-3-25 12:32:31 | 只看該作者
24#
發(fā)表于 2025-3-25 17:33:56 | 只看該作者
Conference proceedings 2023cember 2022...The total of 277 contributions included in the proceedings set was carefully reviewed and selected from 836 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:..Part I: 3D computer vision; optimization methods;.Part II: applications of
25#
發(fā)表于 2025-3-25 22:48:23 | 只看該作者
26#
發(fā)表于 2025-3-26 03:50:18 | 只看該作者
Lecture Notes in Computer Scienceion of faces to approximate head pose. The experimental results indicate that the proposed method exhibits robust gaze estimation performance even in low-resolution face images with 28.28 pixels. The source code of this work is available at ..
27#
發(fā)表于 2025-3-26 07:27:07 | 只看該作者
28#
發(fā)表于 2025-3-26 11:13:22 | 只看該作者
Few-shot Metric Learning: Online Adaptation of?Embedding for?Retrievalset, .DeepFashion, demonstrate that our method consistently improves the learned metric by adapting it to target classes and achieves a greater gain in image retrieval when the domain gap from the source classes is larger.
29#
發(fā)表于 2025-3-26 13:21:22 | 只看該作者
HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in?Low-Resolution Face Imagesion of faces to approximate head pose. The experimental results indicate that the proposed method exhibits robust gaze estimation performance even in low-resolution face images with 28.28 pixels. The source code of this work is available at ..
30#
發(fā)表于 2025-3-26 17:21:59 | 只看該作者
Continuous Self-study: Scene Graph Generation with?Self-knowledge Distillation and?Spatial Augmentathod is adopted to augment spatial features and supplement relationship information. On the Visual Genome benchmark, experiments show that the proposed CSS achieves obvious improvements over the previous state-of-the-art methods. Our code is available at ..
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