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10 PAMIs and 28 CVPRs in just over a year
The AIML (formally ACVT) has had 10 journal articles published in IEEE Pattern Analysis and Machine Intelligence, and 28 papers in the IEEE Conference on Computer Vision and Pattern Recognition, in the 16 months since January 2015.
Great Imagenet detection results
Last week was the deadline for the ImageNet Large Scale Visual Recognition Challenge (ILSVRC 2015) large-scale object detection task. This is the primary challenge for image-based object detection. The challenge requires that you detect 200 classes of objects in a set of test images.
State of the art protein-protein interaction prediction
In another indication that the Machine Learning behind most Computer Vision Problems has more general applicability, we have just had a paper accepted which shows that the approach we developed for pedestrian detection achieves the world鈥檚 best performance in predicting protein-protein interactions.
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In deep learning end-to-end training of segmentation is best
A research team (Dr. Guosheng Lin, Prof. Chunhua Shen, Prof. Ian Reid, Prof. Anton van den Hengel) at the School of Computer Science, The University of 黑料社区 developed innovative 鈥淒eep Structured Learning鈥 techniques that set up the new state-of-the-art semantic image segmentation record in the PASCAL VOC Challenge, which is organised by the University of Oxford. The 黑料社区 team is the top one currently, outperforming teams from Microsoft Research, Oxford, University of California, Los Angles etc.
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Second Scenes from Video workshop to be held in Chile
Michael Black and Anton van den Hengel are organising the , which will be held in the Colchagua Valley, one of Chile鈥檚 pre-eminent wine regions, and will include a variety of functions and excursions exploring the region and its fare.
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Professor Wojciech Chojnacki granted Polish State Professorship
Prof. Wojciech Chojnacki was recently awarded the permanent state title of Professor conferred by the President of the Republic of Poland.
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World's best Coco
The Microsoft COCO Captioning Challenge is designed to spur the development of algorithms producing image captions that are informative and accurate.
AIML semantic image segmentation technique tops the PASCAL VOC Challenge
Researchers at AIML (formerly ACVT) have developed new 鈥淒eep Structured Learning鈥 techniques that set up the new state-of-the-art semantic image segmentation record in the PASCAL VOC Challenge, which is organised by Oxford University. Semantic image segmentation is one of the tasks and probably the most challenging one, which is to label each pixel in images.
[Read more about AIML semantic image segmentation technique tops the PASCAL VOC Challenge]
CVPR 2015 Best Workshop Paper Award
In conjunction with the success of the Australian Centre for Robotic Vision鈥檚 workshops at CVPR2015 in Boston: