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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’s best performance in predicting protein-protein interactions. This result is based on the data set labelled ‘Physical Interaction Task in […]

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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. This is the highest academic title in Poland granted for internationally recognised scientific achievements. The award is conferred upon an extensive and rigorous review process.   Congratulations Wojciech!           Credit: […]

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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. There are 18 teams all together and our attributes based image captioning framework currently achieves the best result on 3 evaluation metrics (BLEU-1,2,3) out of 7. We also achieve the top-5 ranking on the […]

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ACVT semantic image segmentation technique tops in the PASCAL VOC Challenge

Researchers at ACVT have developed new “Deep Structured Learning” 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. Deep Learning is the […]

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CVPR 2015 Best Workshop Paper Award

In conjunction with the success of the Australian Centre for Robotic Vision’s workshops at CVPR2015 in Boston: Workshop on Semantics for Visual Reconstruction, Localization and Mapping Workshop on Visual Place Recognition in Changing Environments An ACRV team was also successful in attaining the Best Workshop Paper Award for the IEEE – Workshop on Computer Vision […]

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Honourable paper at CVPR’15

Congratulations to TJ, Pulak, Anders and David. Their paper, Efficient Globally Optimal Consensus Maximisation with Tree Search, recently was awarded a Best Paper Honourable Mention at CVPR. CVPR is the premier annual conference for Computer Vision research, and this recognition is a fantastic achievement for the team! Only 3 Best Paper Honourable Mention awards were […]

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Twelve papers at CVPR

The ACVT had 12 papers accepted to IEEE Computer Vision and Pattern Recognition 2015 (CVPR’15), one of the top 2 conferences in Computer Vision, which must be an Australian record. In terms of h5-index, CVPR ranks as the 7th venue in all Engineering and Computer Science after Nano and Nature journals. To put this in […]

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Post-Doctoral Research Fellowship in Visual Mapping

Post-Doctoral Research Fellowship in Visual Mapping Australian Centre for Visual Technologies, School of Computer Science, University of Adelaide www.acvt.com.au The Australian Centre for Visual Technologies (ACVT) is seeking an individual to work on an exciting project in conjunction with industrial partner Maptek Pty Ltd to develop next generation systems for real-time mapping of mines.  The […]

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Post-doctoral researcher positions to work on large-scale image classification using deep learning

The Australian Centre for Visual Technologies (ACVT) has two vacancies for post-doctoral researchers to work on deep learning with applications to large-scale image classification, such as on the ImageNet dataset. Successful applicants will have the opportunity to work with the world-class team of researchers on some of the most fundamental, and challenging problems in Computer […]

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Best Paper Award for Prof Ian Reid at 3DV2014

Professor Ian Reid and colleagues from Oxford have been awarded the Best Paper Award at the International Conference on 3D Vision, held in Tokyo, Japan from 8-11 December 2014 The paper, titled “3D Tracking of Multiple Objects with Identical Appearance using RGB-D Input”, was authored by Carl Yuheng Ren, Victor Prisacariu, Olaf Kaehler, Ian Reid […]

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