Titlebook: Computer Vision – ECCV 2024; 18th European Confer Ale? Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

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書(shū)目名稱Computer Vision – ECCV 2024影響因子(影響力)




書(shū)目名稱Computer Vision – ECCV 2024影響因子(影響力)學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2024網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Computer Vision – ECCV 2024網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2024被引頻次




書(shū)目名稱Computer Vision – ECCV 2024被引頻次學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2024年度引用




書(shū)目名稱Computer Vision – ECCV 2024年度引用學(xué)科排名




書(shū)目名稱Computer Vision – ECCV 2024讀者反饋




書(shū)目名稱Computer Vision – ECCV 2024讀者反饋學(xué)科排名

大漩渦

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Jogging

,Self-supervised Visual Learning from?Interactions with?Objects,od consistently outperforms previous methods on downstream category recognition. In our analysis, we find that the observed improvement is associated with a better viewpoint-wise alignment of different objects from the same category. Overall, our work demonstrates that embodied interactions with obj

串通

,BAFFLE: A Baseline of?Backpropagation-Free Federated Learning,BAFFLE only execute forward propagation and return a set of scalars to the server. Empirically we use BAFFLE to train deep models from scratch or to finetune pretrained models, achieving acceptable results.

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legislate

,Omni6DPose: A Benchmark and?Model for?Universal 6D Object Pose Estimation and?Tracking,d ambiguities. To address this issue, we introduce ., an enhanced version of the?SOTA category-level 6D object pose estimation framework, incorporating two pivotal improvements: Semantic-aware feature extraction?and Clustering-based aggregation. Moreover, we provide a comprehensive benchmarking anal

削減

,Style-Extracting Diffusion Models for?Semi-supervised Histopathology Segmentation,, by leveraging styles from unseen images, resulting in more diverse generations.?In this work, we use the image layout as target condition and?first show the capability of our method on a natural image dataset as?a proof-of-concept. We further demonstrate its versatility?in histopathology, where we