Source: https://www.vision.ee.ethz.ch/en/datasets/
Timestamp: 2019-04-24 17:56:49+00:00

Document:
Find below a selection of datasets maintained by us. All data is only for research purposes, unless stated differently. Please make sure to reference the authors properly when using the data.
The dataset, named CVL GeoZurich 2018, consists of about 3 million high-quality images, spanning 70 km in the drive-able street network of Zurich. It consists of a rigid 16 camera setup with 4 stereo pairs and 8 additional view points.
This dataset is not available for the public.
The dataset, named CVL AirZurich 2018, consists of about 830 high-quality aerial images, spanning across the city of Zurich. It consists of GPS-registered flyover path and 16-bit RGB TIFF images.
The dataset, named DAVIS 2017 (Densely Annotated VIdeo Segmentation), consists of 150 high quality video sequences, spanning multiple occurrences of common video object segmentation challenges such as occlusions, motion-blur and appearance changes. Each video is accompanied by densely annotated, pixel-accurate and per-frame ground truth segmentation of multiple objects.
The dataset, named DAVIS 2016 (Densely Annotated VIdeo Segmentation), consists of fifty high quality, Full HD video sequences, spanning multiple occurrences of common video object segmentation challenges such as occlusions, motion-blur and appearance changes. Each video is accompanied by densely annotated, pixel-accurate and per-frame ground truth segmentation of a single object.
F. Perazzi, J. Pont-Tuset, B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung , "A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation", CVPR, 2016.
The IMDB-WIKI dataset contains more than 500k face images with gender and age labels for training. We provide pre-trained models for both age and gender prediction. Our method for age estimation was pre-trained on IMDB-WIKI and is the winner (1st place) of the ChaLearn LAP 2015 challenge on apparent age estimation with more than 115 registered teams, significantly outperforming the human reference.
Rasmus Rothe and Radu Timofte and Luc Van Gool, "Deep expectation of real and apparent age from a single image without facial landmarks", IJCV, 2016.
Rasmus Rothe and Radu Timofte and Luc Van Gool, "DEX: Deep EXpectation of apparent age from a single image", ICCVW, 2015.
A dataset for large-scale texture synthesis. It contains 21,302 texture examples. All of them are annotated in terms of their synthesizability: the ‘goodness’ of the synthesized results by four popular example-based texture synthesis methods.
Dengxin Dai; Riemenschneider, H.; Van Gool, L., "The Synthesizability of Texture Examples", in Computer Vision and Pattern Recognition (CVPR), 2014.
A data set for recognition of pictured dishes. It contains 101 food categories with in total 101'000 images.
Semantical 3D models, e.g. of cities are usually derived from classifying 2D images. The 3D challenge pushes the frontiers on 3D modelling and 3D semantic classification. This dataset consists of 700 meters along a street annotated with pixel-level labels for facade details such as windows, doors, balconies, roof, etc. It is the largest and most detailed dataset available including a dense surface and semantic labels for urban classes.
H. Riemenschneider, A. Bodis-Szomoru, J. Weissenberg, L. Van Gool, "Learning Where To Classify In Multi-View Semantic Segmentation", European Conference on Computer Vision (ECCV'14).
Over 15K images of 20 people recorded with a Kinect while turning their heads around freely. For each frame, depth and rgb images are provided, together with ground in the form of the 3D location of the head and its rotation angles.
G. Fanelli, T. Weise, J. Gall, L. Van Gool, "Real Time Head Pose Estimation from Consumer Depth Cameras", 33rd Annual Symposium of the German Association for Pattern Recognition (DAGM'11).
G. Fanelli, J. Gall, L. Van Gool, "Real Time Head Pose Estimation with Random Regression Forests",Computer Vision and Pattern Recognition (CVPR'11).
The corpus contains high quality dynamic (25 fps) 3D scans of faces recorded while pronouncing a set of English sentences. Affective states were induced by showing emotional video clips to the speakers. The data has been annotated by tracking all frames using a generic face template, segmenting the speech signal into single phonemes, and evaluating the emotions conveyed by the recorded sequences by means of an online survey.
G. Fanelli, J. Gall, H. Romsdorfer, T.Weise, L. Van Gool, "A 3-D Audio-Visual Corpus of Affective Communication",IEEE Transactions on Multimedia, Vol. 12, No. 6, pp. 591 - 598, 2010.
G. Fanelli, J. Gall, H. Romsdorfer, T.Weise, L. Van Gool, "3D Vision Technology for Capturing Multimodal Corpora: Chances and Challenges", LREC WS on Multimodal Corpora, May 2010.
G. Fanelli, J. Gall, H. Romsdorfer, T.Weise, L. Van Gool, "Acquisition of a 3D Audio-Visual Corpus of Affective Speech", Computer Vision Lab, ETH Zuerich, Technical Report no. 270, February 2010.
Walking pedestrians in busy scenarios from a bird eye view. Manually annotated. Data used for training in our ICCV09 paper "You'll Never Walk Alone: Modeling Social Behavior for Multi-target Tracking"
A dataset for testing object class detection algorithms. It contains 255 test images and features five diverse shape-based classes (apple logos, bottles, giraffes, mugs, and swans).
V. Ferrari, F. Jurie, and C. Schmid "From Images to Shape Models for Object Detection", International Journal of Computer Vision (IJCV), 2009.
V. Ferrari, T. Tuytelaars, and L. Van Gool "Object Detection by Contour Segment Networks", European Conference on Computer Vision (ECCV), Graz, May 2006.
T. Quack, V. Ferrari, B. Leibe, L. Van Gool "Efficient Mining of Frequent and Distinctive Feature Configurations", International Conference on Computer Vision (ICCV), 2007.
The Extended ETHZ shape classes is a larger database of shape categories, created by merging ETHZ shape classes with Konrad Schindler's 4x50 closed shapes. This is (almost) a superset of each of the two older databases. Please refer to the README for details on the differences and how to use the new larger dataset.
K. Schindler and D. Suter."Object Detection by Global Contour Shape", Pattern Recognition, 41(12), 2008.
Range images of faces with ground truth used in our CVPR'08 paper "Real-Time Face Pose Estimation from Single Range Images".
Dataset used in our CVPR '07 paper "Dynamic 3D Scene Analysis from a Moving Vehicle"
The sequence contains 1175 stereo camera pairs acquired with setup mounted on top of a moving vehicle. The stereo setup has a fixed baseline, and the cameras are calibrated internally and with respect to each other.
Three pedestrian crossing sequences used in our ICCV'07 paper. Each sequence comes with ground-truth bounding box annotations for the objects to be tracked, as well as a camera calibration. The annotation files for the pedestrian crossing sequences contain bounding box annotations for every fourth frame.
Dataset used in our ICCV '07 paper "Depth and Appearance for Mobile Scene Analysis"
The set was recorded in Zurich, using a pair of cameras mounted on a mobile platform. It contains 12'298 annotated pedestrians in roughly 2'000 frames.
The goal of the ZuBuD Image Database is to share image data sets with researcheres around the world. To facilitate this, we have created this site, which contains over 1005 images about Zurich city building. The detail information about the database can be found on our Technical Report:TR-260.
We will be adding new data to this site as time permits. Furthermore, we will now accept datasets from other researchers, to add to our archive. If you would like to contribute for this, please contact Hao Shao. The full sized images themselves are stored in PNG (Portable Network Graphics) format.
the motion fields for different breathing cycles of different subjects. Point trajectories for isotropic grids of 15mm and 5mm are provided in both plain text and binary format.
a reconstructed MRI volume per subject at exhalation in Analyze (*.hdr/img), Dicom (*.dcm) and MATLAB (*.mat) format.
available. There's also code to be able to read in our registration results. These datasets were used in our publication available here.
Boye, D. et al. - Population based modeling of respiratory lung motion and prediction from partial information - Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86690U (March 13, 2013); doi:10.1117/12.2007076.
Code for reading registration results.
A data set for recognition of events in personal photo collections. It contains more than 61'000 images in 807 collections, annotated with 14 diverse social event classes.
L. Petrusca, P. Cattin, V. De Luca, F. Preiswerk, Z. Celicanin, V. Auboiroux, M. Viallon, P. Arnold, F. Santini, S. Terraz, K. Scheffler, C. D. Becker, R. Salomir, "Hybrid Ultrasound/Magnetic Resonance Simultaneous Acquisition and Image Fusion for Motion Monitoring in the Upper Abdomen", Investigative Radiology, Vol. 48, No. 5, pp. 333-340, 2013.
V. De Luca, M. Tschannen, G. SzÃ©kely, C. Tanner, "A Learning-based Approach for Fast and Robust Vessel Tracking in Long Ultrasound Sequences", Medical Image Computing and Computer-Assisted Intervention, Springer. volume of LNCS 8149, pp. 518-525, 2013.

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