Thursday, August 22, 2019
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Congratulations! One paper will be published in ACM Transactions on Multimedia Computing, Communications, and Applications

Congratulations to Shih-Yao Lin, Yen-Yu Lin, Chu-Song Chen, and Yi-Ping Hung! Our work entitled "Recognizing Human Actions with Outlier Frames by Observation Filtering and Completionhas been accepted for ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM).

 

Congratulations! One paper was accepted by CVPR 2017

Congratulations to Ya-Fang Shih*, Yang-Ming Yeh*, Yen-Yu Lin, Yi-Chang Lu, Ming-Feng Weng, and Yung-Yu Chuang! Our work entitled "Deep Co-occurrence Feature Learning for Visual Object Recognition" has been accepted for CVPR 2017. (*: equal contribution)

 

Congratulations! Two papers were accepted by ICME 2017

Congratulations to Chung-Chi Tsai, Xiaoning Qian, and Yen-Yu Lin! Our work entitled "Segmentation Guided Local Proposal Fusion for Co-saliency Detection" has been accepted for ICME 2017.

Congratulations to Mettu Srinivas, Yen-Yu Lin, and Hong-Yuan Mark Liao! Our work entitled "Learning Deep And Sparse Feature Representation for Fine-grained Eecognition" has been accepted for ICME 2017.

 

Congratulations! Two papers were accepted by ICASSP 2017

Congratulations to Chung-Chi Tsai, Xiaoning Qian, and Yen-Yu Lin! Our work entitled "Image Co-Saliency Detection via Locally Adaptive Saliency Map Fusion" has been accepted for ICASSP 2017.

Congratulations to Shih-Yao Lin, Yen-Yu Lin, Chu-Song Chen, and Yi-Ping Hung! Our work entitled "Learning and Inferring Human Actions with temporal Pyramid Features based on Conditional Random Fields" has been accepted for ICASSP 2017.

 

Congratulations! One paper will be published in International Conference on Pattern Recognition

Congratulations to Chun-Rong Huang, Wei-An Wang, Szu-Yu Lin and Yen-Yu Lin! Our work entitled "USEQ: Ultra-Fast Superpixel Extraction via Quantization" has been accepted for International Conference on Pattern Recognition (ICPR).

 

Congratulations! One paper will be published in IEEE Trans. on Image Processing

Congratulations to Pai-Heng Hsiao, Feng-Ju Chang, and Yen-Yu Lin! Our work entitled "Learning Discriminatively Reconstructed Source Data for Object Recognition with Few Examples" has been accepted for IEEE Transactions on Image Processing (TIP).