The PKU-Spike-A dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation. The goals to create the PKU-Spike-A include:
(1) providing the worldwide researchers of the spike coding community a large-scale spike dataset for evaluating their coding algorithms;
(2) facilitating the development of high-efficient spike coding technologies by providing large-scale spike sequences with different depth of field or at different luminance and time conditions.
Therefore, the PKU-Spike-A dataset is now partly made available for the academic purpose only on a case-by-case basis. The first available part contains Class A (normal speed) and Class B (high speed) with six spike sequences in total. More sequences are under evaluation which will be public available in the near future.

The PKU-Spike-A dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation. The NELVT at Peking University is serving as the technical agent for distribution of the dataset and reserves the copyright of all the sequences in the dataset. Any researcher who requests the PKU-Spike-A dataset must sign this agreement and thereby agrees to observe the restrictions listed in this document. Failure to observe the restrictions will result in access being denied for the request of the future version of the PKU-Spike-A dataset and being subject to civil damages in the case of publication of sequences that have not been approved for release.

LICENSE

• The spike sequences for download are part of the PKU-Spike-A dataset.
• The sequences can only be used for ACADEMIC PURPOSES. NO COMERCIAL USE is allowed.
• Copyright © National Engineering Laboratory for Video Technology (NELVT) and Institute of Digital Media, Peking University (PKU-IDM). All rights reserved.

Download

• You can download the agreement(pdf) by clicking the DOWNLOAD link (available soon).
• After filling it, please send the electrical version to our Email: pkuml at pku.edu.cn (Subject: PKU-Spike-A Agreement) and mail the paper version to our lab: Room 2604, Science Building No. 2, Peking University, No.5 Yiheyuan Road, Haidian District, Beijing, P.R.China .

The PKU-DVS dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation. The goals to create the PKU-DVS include:
(1) providing the worldwide researchers of the spike coding community a large-scale DVS spike dataset for evaluating their coding algorithms;
(2) facilitating the development of high-efficient spike coding technologies by providing large-scale spike sequences with different depth of field or at different luminance and time conditions.
Therefore, the PKU-DVS dataset is now partly made available for the academic purpose only on a case-by-case basis. The first available part contains Class A (indoor) and Class B (outdoor) with seven and six spike sequences, respectively. More sequences are under evaluation which will be public available in the near future.

The PKU-DVS dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation. The NELVT at Peking University is serving as the technical agent for distribution of the dataset and reserves the copyright of all the sequences in the dataset. Any researcher who requests the PKU-DVS dataset must sign this agreement and thereby agrees to observe the restrictions listed in this document. Failure to observe the restrictions will result in access being denied for the request of the future version of the PKU-DVS dataset and being subject to civil damages in the case of publication of sequences that have not been approved for release.

The PKU HumanDI dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation.

This dataset is composed of videos subjects crossing 11 cameras in a campus. It includes 6 high definition network cameras (Camera HD01, Camera HD02, Camera HD03, Camera HD04, Camera HD05, Camera HD06) and 7 normal network cameras (Camera BWBQ, Camera DCM, Camera WMHD, Camera XDMN, Camera YGLN, Camera YGLQ, Camera YTX). Some samples of the labeled results are shown below:

HD Cameras (HD 01, HD 02, HD 04, HD 06)

Normal Cameras (WMHD, DCM, YTX, YGLN)

The PKU HumanID dataset is now partly made available for the academic purpose only on a case-by-case basis. The NELVT at Peking University is serving as the technical agent for distribution of the dataset and reserves the copyright of all the videos in the dataset. Any researcher who requests the PKU HumanID dataset must sign this agreement and thereby agrees to observe the restrictions listed in this document.

LICENSE

• The videos and the corresponding annotation results for download are part of PKU HumanID.
• The videos and the corresponding annotation results can only be used for ACADEMIC PURPOSES. NO COMERCIAL USE is allowed.
• Copyright © National Engineering Laboratory for Video Technology (NELVT) and Institute of Digital Media, Peking University (PKU-IDM). All rights reserved.

All publications using PKU HumanID dataset should cite the paper below:

• Lan Wei, Yonghong Tian, Yaowei Wang, Tiejun Huan, Swiss-System Based Cascade Ranking for Gait-based Person Re-identification, 29th AAAI Conference on Artificial Intelligence, Austin Texas, USA, January, 2015

DOWNLOAD

You can download the agreement (pdf) by clicking the DOWNLOAD link.

After filling it, please send the electrical version to our Email: pkuml at pku.edu.cn (Subject: PKU-HumanID-Agreement)

After confirming your information, we will send the download link and password to you via Email. You need to follow the agreement.

An implementation of “Wang M, Konrad J, Ishwar P, Jing K, Rowley H (2011) Image saliency: From intrinsic to extrinsic context. CVPR, 2011.”

Re-implemented by Jia Li (jiali@buaa.edu.cn) and Shu Fang (sfang@pku.edu.cn).

Code folder: contains our implementation of (Wang et al. 2011) and the metrics for computing AUC, EOF and FS. More details can be found in our paper submitted to IJCV (J. Li et al. Measuring Visual Surprise Jointly from Intrinsic and Extrinsic Contexts for Image Saliency Estimation)

MIT1003 folder: the data used for testing (Wang et al. 2011). Subfolder “image” contains all the images from the dataset MIT1003, and subfolder “refImages” contains all the 20 most similar images retrieved from a large database with 31.2 million images.

Result folder: three subfolders, IES_intSal, IES_extSal and IES, contain the saliency maps from intrinsic context, extrinsic context and both contexts, respectively.

Code:
/mlg/download/code/wang11.zip
/mlg/download/code/wang11-codeResult.zip

We constructed this PKU-RSD (Regional Saliency Dataset) dataset that could capture spatiotemporal visual saliency for evaluating different video saliency models. This dataset contains 431 short videos, which cover various scenes (surveillance, ad, news, cartoon, movie etc.) and the corresponding annotation results of salient objects in sampled key frames manually labeled by 23 subjects. Some samples of the annotation results are shown below:

LICENSE

• The videos and the corresponding annotation results for download are part of PKU-RSD (Regional Saliency Dataset) dataset.
• The videos and the corresponding annotation results can only be used for ACADEMIC PURPOSES. NO COMERCIAL USE is allowed.
• Copyright © National Engineering Laboratory for Video Technology (NELVT) and Institute of Digital Media, Peking University (PKU-IDM). All rights reserved.

All publications using PKU-RSD should cite the paper below:

• Jia Li, Yonghong Tian, Tiejun Huang, Wen Gao. A DATASET AND EVALUATION METHODOLOGY FOR VISUAL SALIENCY IN VIDEO. ICME 2009

DOWNLOAD
You can download the agreement (pdf) by clicking the DOWNLOAD link.
After filling it, please send the electrical version to our Email: pkuml at pku.edu.cn (Subject: PKU-RSD Agreement)
After confirming your information, we will send the download link and password to you via Email. You need to follow the agreement.

To compare the performances of different enhancement algorithms, we constructed this PKU-EAQA (Peking University Enhancement Algorithm Quality Assessment) dataset. This dataset contains 300 images in bad visibility (in haze, low light, etc.), 1500 enhanced images generated by different enhancement algorithms and their subjective quality assessment results.

LICENSE

• The images and the subjective quality assessment results for download are part of PKU-EAQA (Peking University Enhancement Algorithm Quality Assessment) dataset.
• The images and the subjective quality assessment results can only be used for ACADEMIC PURPOSES. NO COMERCIAL USE is allowed.
• Copyright © National Engineering Laboratory for Video Technology (NELVT) and Institute of Digital Media, Peking University (PKU-IDM). All rights reserved.

All publications using PKU-EAQA should cite the papers below:

• Zhengying Chen, Tingting Jiang, Yonghong Tian, Quality Assessment for Comparing Image Enhancement Algorithms. To appear in IEEE Conference on Computer Vision and Pattern Recognition, 2014.

DOWNLOAD
You can download the agreement(pdf) by clicking the DOWNLOAD link.
After filling it, please send the electrical version to our Email: pkuml at pku.edu.cn (Subject: PKU-EAQA Agreement) After confirming your information, we will send the download link and password to you via Email. You need to follow the agreement.

The PKU-VISUAL-OBJECTS dataset is constructed by National Engineering Laboratory for Video Technology (NELVT), Peking University, sponsored by the National Basic Research Program of China and Chinese National Natural Science Foundation.
the PKU-VISUAL-OBJECTS dataset is now partly made available for the academic purpose only on a case-by-case basis. The NELVT at Peking University is serving as the technical agent for distribution of the dataset and reserves the copyright of all the videos in the dataset. Any researcher who requests the PKU-VISUAL-OBJECTS dataset must sign this agreement and thereby agrees to observe the restrictions listed in this document. Failure to observe the restrictions will result in access being denied for the request of the future version of the PKU-VISUAL-OBJECTS dataset and being subject to civil damages in the case of publication of videos that have not been approved for release.

VIDEO MASKS

Resolution	Sequence	Frames	Mask
1080p	Kimono	238
	ParkScene	238
	BasketballDrive	499
720p	Johnny	598
	KristenAndSara	598
	FourPeople	598

LICENSE

• The videos for download is part of PKU-VISUAL-Objects Dataset.
• The videos can only be used for ACADEMIC PURPOSES. For COMERCIAL USE, please contact us for authorization .
• Copyright © National Engineering Laboratory for Video Technology (NELVT) and Institute of Digital Media, Peking University (PKU-IDM). All rights reserved.

All publications using PKU-VISUAL-OBJECTS Dataset should cite the paper below:

• Tiejun Huang, Siwei Dong, Yonghong Tian, Representing Visual Objects in HEVC
  Coding Loop, IEEE Journal on Emerging and Selected Topics in Circuits and
  Systems, Volume 4, Issue 1, March 2014, 5-16. DOI:
  10.1109/JETCAS.2014.2298274.

Download

• You can download the agreement(pdf) by clicking the DOWNLOAD link.
• After filling it, please send the electrical version to our Email: pkuml at pku.edu.cn (Subject: PKU-VISUAL-OBJECTS Dataset Agreement)
• The original videos (without masks) are part of HEVC/H.265 common test sequences, which can be downloaded from JCT-VC FTP (ftp://hevc@ftp.tnt.uni-hannover.de/testsequences).

• PKU-Masked-Face Dataset
• PKU-EAQA Dataset
• PKU-DVS Dataset
• PKU-HumanID Dataset
• PKU-RSD Dataset
• PKU-SVD-A Dataset
• PKU-VehicleID Dataset
• PKU-VD Dataset
• PKU-VISUAL-OBJECTS Dataset
• PKU SketchRe-ID Dataset
• PKU-DDD17-CAR Dataset
• PKU-Spike-High-Speed Dataset
• PKU-Spike-Recon Dataset
• PKU-AIR300 Dataset
• PKU-RETINA-RECON Dataset
• PKU-Vidar-DVS Dataset
• PKU-DAVIS-SOD Dataset