Research Focus

The prevalence of capture devices and the advent of media-sharing services have drastically increased the sheer amount of image and video collections. Here arise the strong needs for effective multimedia analysis and efficient multimedia retrieval. We have been devoted to large-scale photo and video retrieval, knowledge discovery from large-scale social media mining, distributed computation for multimedia analysis and retrieval, and devised novel multimedia applications in mobile devices.

Recently, we focus on numerous Deep Convolutional Neural Network methods for large-scale image/video analysis and retrieval projects, sponsored by leading industry partners (Microsoft Research, MediaTek, HTC, etc.). Especially, we aim for effective CNN methods for image/video applications such as image search, video event detection, face recognition,  facial/clothing attributes, super-resolution, etc.

Though having observed very exciting applications in large-scale multimedia analysis and retrieval, we further identify certain core challenges and respond to them respectively:

  facial/clothing attribute detection/search
web-scale indexing & feature learning
large-scale photo/video recognition
web-scale facial image retrieval
mobile visual recognition

multimodal deep neural network
social media mining
big data analytics and visualization
first-person/wearable cameras
consumer photo retrieval


Research Sponsors for MiRA


   nsc  cyberlink  ntuitri


iii   chttl   microsoft sneergy MStarQuanta Computerquanta research Academia Sinica Taiwan Mobile MediaTek HTC


Honors and Awards