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

喜悅

書目名稱Computer Vision – ECCV 2018影響因子(影響力)




書目名稱Computer Vision – ECCV 2018影響因子(影響力)學(xué)科排名




書目名稱Computer Vision – ECCV 2018網(wǎng)絡(luò)公開度




書目名稱Computer Vision – ECCV 2018網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Vision – ECCV 2018被引頻次




書目名稱Computer Vision – ECCV 2018被引頻次學(xué)科排名




書目名稱Computer Vision – ECCV 2018年度引用




書目名稱Computer Vision – ECCV 2018年度引用學(xué)科排名




書目名稱Computer Vision – ECCV 2018讀者反饋




書目名稱Computer Vision – ECCV 2018讀者反饋學(xué)科排名

Paleontology

In-Situ

transdermal

Pairwise Body-Part Attention for Recognizing Human-Object Interactions region. They ignore the fact that normally, human interacts with an object by using some parts of the body. In this paper, we argue that different body parts should be paid with different attention in HOI recognition, and the correlations between different body parts should be further considered. T

obviate

LATHE

LATHE

anaphylaxis

Learning Class Prototypes via Structure Alignment for Zero-Shot Recognitione semantic information and auxiliary datasets. Recently most . approaches focus on learning visual-semantic embeddings to transfer knowledge from the auxiliary datasets to the novel classes. However, few works study whether the semantic information is discriminative or not for the recognition task.

裁決

綁架

DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNsill suffer from heavy noises which limit their applications. Although plenty of progresses have been made to reduce the noises and boost geometric details, due to the inherent illness and the real-time requirement, the problem is still far from been solved. We propose a cascaded Depth Denoising and