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

Cupping

BET

Introduction to Alternative Assessment,t-time adaptation. While typical approaches rely on a large amount of demonstration data for such generalization, we propose an approach that leverages web videos to predict plausible interaction plans and learns a task-agnostic transformation to obtain robot actions in the real world. Our framework

miniature

Farrah Dina Yusop,Amira Firdausmited by the large computational cost of volumetric rendering. Recently, 3D Gaussian Splatting emerged as a much faster alternative with superior rendering quality and training efficiency, especially for small-scale and object-centric scenarios. Nevertheless, this technique suffers from poor perform

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Conference proceedings 2025nt learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation..

顧客

0302-9743 reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation..978-3-031-73115-0978-3-031-73116-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

enormous

雪上輕舟飛過

Developments in Hematology and Immunologyom the categorical counting module to dynamically adjust the number and positional information of object queries. Our model DQ-DETR outperforms previous CNN-based and DETR-like methods, achieving state-of-the-art mAP 30.2% on the AI-TOD-V2 dataset, which mostly consists of tiny objects. Our code will be available at ..

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性學院

,SIMBA: Split Inference—Mechanisms, Benchmarks and?Attacks,ction techniques for evaluating their privacy-utility trade-off. Finally, we release a dataset of obfuscated representations to foster research in this area. We have open-sourced code, dataset, hyper-parameters, and trained models that can be found at ..

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,DQ-DETR: DETR with?Dynamic Query for?Tiny Object Detection,om the categorical counting module to dynamically adjust the number and positional information of object queries. Our model DQ-DETR outperforms previous CNN-based and DETR-like methods, achieving state-of-the-art mAP 30.2% on the AI-TOD-V2 dataset, which mostly consists of tiny objects. Our code will be available at ..