Titlebook: Computer Vision – ECCV 2018; 15th European Confer Vittorio Ferrari,Martial Hebert,Yair Weiss Conference proceedings 2018 Springer Nature Sw

PTCA635

Spyros Blavoukos,Dimitris Bourantonists in large-scale detection benchmarks (.?the COCO dataset), the performance on small objects is far from satisfactory. The reason is that small objects lack sufficient detailed appearance information, which can distinguish them from the background or similar objects. To deal with the small object d

EPT

Pelago

arrogant

Alexander Antonov,Tanel Kerikm?epublicly available large diverse datasets. In this paper, we introduce CCPD, a large and comprehensive LP dataset. All images are taken manually by workers of a roadside parking management company and are annotated carefully. To our best knowledge, CCPD is the largest publicly available LP dataset t

一大塊

lanugo

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234196.jpg

改良

女歌星

大洪水

https://doi.org/10.1007/978-1-84800-171-8 using a batch size of 2; when using typical batch sizes, GN is comparably good with BN and outperforms other normalization variants. Moreover, GN can be naturally transferred from pre-training to fine-tuning. GN can outperform its BN-based counterparts for object detection and segmentation in COCO,

Mangle