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Titlebook: Computer Vision – ECCV 2016; 14th European Confer Bastian Leibe,Jiri Matas,Max Welling Conference proceedings 2016 Springer International P

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樓主: 傳家寶
21#
發(fā)表于 2025-3-25 06:46:19 | 只看該作者
22#
發(fā)表于 2025-3-25 08:25:11 | 只看該作者
DAVE: A Unified Framework for Fast Vehicle Detection and Annotationchieve efficient vehicle detection and annotation for real-world traffic surveillance data. We evaluate DAVE on a new self-collected UTS dataset and the public PASCAL VOC2007 car and LISA 2010 datasets, with consistent improvements over existing algorithms.
23#
發(fā)表于 2025-3-25 15:12:14 | 只看該作者
24#
發(fā)表于 2025-3-25 16:59:45 | 只看該作者
Modeling Context in Referring Expressionshe language generation process together, so that we generate expressions for all objects of a particular category jointly. Evaluation on three recent datasets - RefCOCO, RefCOCO+, and RefCOCOg (Datasets and toolbox can be downloaded from .), shows the advantages of our methods for both referring expression generation and comprehension.
25#
發(fā)表于 2025-3-25 22:09:54 | 只看該作者
26#
發(fā)表于 2025-3-26 01:33:02 | 只看該作者
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發(fā)表于 2025-3-26 07:08:39 | 只看該作者
28#
發(fā)表于 2025-3-26 11:39:23 | 只看該作者
29#
發(fā)表于 2025-3-26 14:01:58 | 只看該作者
30#
發(fā)表于 2025-3-26 20:44:47 | 只看該作者
https://doi.org/10.1057/978-1-137-46839-0sed of hazy images and corresponding transmission maps based on the NYU Depth dataset. Extensive experiments demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods on both synthetic and real-world images in terms of quality and speed.
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