Control-Group
发表于 2025-3-30 09:46:01
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Antagonism
发表于 2025-3-30 14:44:28
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Albinism
发表于 2025-3-30 19:49:03
Stream-Based Active Unusual Event Detection methods that perform passive mining for unusual events, our approach automatically requests supervision for critical points to resolve ambiguities of interest, leading to more robust and accurate detection on subtle unusual events. The active learning strategy is formulated as a stream-based soluti
身体萌芽
发表于 2025-3-30 22:10:02
Asymmetric Totally-Corrective Boosting for Real-Time Object Detectiontandard for this problem. In this framework, the learning goal for each node is asymmetric, which is required to achieve a high detection rate and a moderate false positive rate. We develop new boosting algorithms to address this asymmetric learning problem. We show that our methods explicitly optim
Frequency-Range
发表于 2025-3-31 03:59:29
The Application of Vision Algorithms to Visual Effects Productioneir early ages, it still requires constant innovation and in many cases a great amount of craftsmanship. Given these premises, most VFX companies (especially those at the leading edge) are hungry for novel and better solutions to the problems they encounter everyday. Many published machine vision al
Exaggerate
发表于 2025-3-31 08:33:05
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thrombus
发表于 2025-3-31 11:46:07
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我说不重要
发表于 2025-3-31 14:30:09
Finding Human Poses in Videos Using Concurrent Matching and Segmentationr image, the proposed method detects the poses of a specific human subject in long video sequences. Matching and segmentation support each other and therefore the simultaneous optimization enables more reliable results. However, efficient concurrent optimization is a great challenge due to its huge
抛物线
发表于 2025-3-31 18:06:38
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重画只能放弃
发表于 2025-3-31 23:21:36
Deformable Object Modelling and Matchingve an overview of such models and of two efficient algorithms for matching such models to new images (Active Shape Models and Active Appearance Models). We also describe recent work on automatically constructing such models from minimally labelled training images.