Titlebook: Advances in Multimedia Information Processing – PCM 2017; 18th Pacific-Rim Con Bing Zeng,Qingming Huang,Xiaopeng Fan Conference proceedings

極大痛苦

An Introduction to Cooperativesxperimental results demonstrate that our method significantly outperform previous baseline SCRC (Spatial Context Recurrent ConvNet) [.] model on Referit dataset [.], moreover, our model is simple to train similar to Faster R-CNN.

侵略主義

Negotiate

特征

休息

podiatrist

An Efficient Feature Selection for SAR Target Classificationnt features. Finally, for target classification, SVM is used as a baseline classifier. Experiments on MSTAR public release dataset are conducted, and the results demonstrate that the proposed method outperforms the state-of-the-art methods.

cunning

Automatic Foreground Seeds Discovery for Robust Video Saliency Detectionobal object appearance model using the initial seeds and remove unreliable seeds according to foreground likelihood. Finally, the seeds work as queries to rank all the superpixels in images to generate saliency maps. Experimental results on challenging public dataset demonstrate the advantage of our algorithm over state-of-the-art algorithms.

FID

intercede

Object Discovery and Cosegmentation Based on Dense Correspondencessides, due to the powerful feature learning ability of deep models, we adopt VGG features to do unsupervised clustering and find representative candidates as a prior knowledge. Experiments on noisy datasets show the effectiveness of our method.

服從

Fusing Appearance Features and Correlation Features for Face Video Retrievalnd hash learning into a unified optimization framework to guarantee optimal compatibility of appearance features and correlation features. Experiments on two challenging TV-Series datasets demonstrate the effectiveness of the proposed method.