News: Research

Another great CVPR result

The group had 11 CVPR papers accepted this year, which is another incredible result.

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Number one in Semantic Segmentation

VoQ

Congratulations to Zifeng Wu and Chunhua Shen on having made it to the top of the Cityscapes leaderboard again.

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A new Machine Learning result in Quantum Physics

Quantum

John Bastian and Anton van den Hengel are among the authors of a new paper just published in Nature Scientific Reports.

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We're in the top 5 groups the world

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) is double blind reviewed (on full papers), and has the best citation rate in the field of computer vision and pattern recognition, according to the h5-index, a citation measure for the recent five years.

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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.

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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.

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In deep learning end-to-end training of segmentation is best

Segmentation

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 Adelaide developed innovative “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 the University of Oxford.  The Adelaide team is the top one currently, outperforming teams from Microsoft Research, Oxford, University of California, Los Angles etc.

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