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Alice Benchmarks
Alice is an online evaluation server that contains a series of domain adaptation tasks in computer vision. The source is simulated data; the target is real or synthetic data.
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domain adaptive pedestrian recognition
More tasks are coming, aiming at content-level domain adaptation. That is, the source domain is editable through graphics engines.


PersonX engine
This is a data synthesis engine capable of generating persons under controllable environmental conditions. That is, the illumination, viewpoint, camera settings can be edited precisely. In our CVPR19 paper, it is used to assess the impact of environmental factors on the system accuracy.
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Market-1501 dataset
This dataset is collected and annotated in Tsinghua. It has 6 cameras, 1,501 IDs and a distractor set of 500k images. Only one train/test split is used. We also annotate the ID-level attributes for Market-1501.
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attributes
state of the art on Market-1501
state of the art on Market-1501+500k

CUHK03 dataset with new evaluation protocol
We have used a new evaluation protocol for the CUHK03 dataset. This protocol only has one train/test split instead of the previous 20 train/test splits. The training and testing sets have 767 and 700 IDs, respectively.
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MARS dataset
This dataset is a video extension of Market-1501. It has 6 cameras and 1,261 IDs. Only one train/test split is used.
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state of the art on MARS

PRW dataset
This dataset is another extension of Market-1501. It provides 11,816 video frames. We draw a bounding box for all the pedestrians. We assign an ID (1-932) to most of them, and -2 to those whose IDs we do not know for sure. For this dataset, one should create a gallery by pedestrian detection and then evaluate person re-identification. Re-ID performance is closely related to detection performance.
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