固执点好
发表于 2025-3-27 00:04:00
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VAN
发表于 2025-3-27 03:01:07
Exploring the Limits of Weakly Supervised Pretraining image classification and object detection tasks, and report the highest ImageNet-1k single-crop, top-1 accuracy to date: 85.4% (97.6% top-5). We also perform extensive experiments that provide novel empirical data on the relationship between large-scale pretraining and transfer learning performance.
Deject
发表于 2025-3-27 08:39:41
3D-CODED: 3D Correspondences by Deep Deformationn the difficult FAUST-inter challenge, with an average correspondence error of 2.88 cm. We show, on the TOSCA dataset, that our method is robust to many types of perturbations, and generalizes to non-human shapes. This robustness allows it to perform well on real unclean, meshes from the SCAPE dataset.
土坯
发表于 2025-3-27 12:36:13
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罗盘
发表于 2025-3-27 16:09:22
0302-9743 ter Vision, ECCV 2018, held in Munich, Germany, in September 2018..The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and re
震惊
发表于 2025-3-27 18:18:16
Research Design and Methodologyy with the percentage of correct labels, so we use it as an inference criterion for the unknown labels, without attempting to infer the model parameters at first. Despite its simplicity, SaaS achieves competitive results in semi-supervised learning benchmarks.
dyspareunia
发表于 2025-3-28 00:06:39
SaaS: Speed as a Supervisor for Semi-supervised Learningy with the percentage of correct labels, so we use it as an inference criterion for the unknown labels, without attempting to infer the model parameters at first. Despite its simplicity, SaaS achieves competitive results in semi-supervised learning benchmarks.
描述
发表于 2025-3-28 02:04:52
Computer Vision – ECCV 2018978-3-030-01216-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
ONYM
发表于 2025-3-28 08:46:21
Structure and Power Redistributiona learning-based approach to generate visually coherent completion given a high-resolution image with missing components. In order to overcome the difficulty to directly learn the distribution of high-dimensional image data, we divide the task into inference and translation as two separate steps and
PET-scan
发表于 2025-3-28 13:23:54
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