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{
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{
            
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  "author": "Max Coenen",
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  "author": "Max Coenen",
            
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  "author_email": "coenen@ipi.uni-hannover.de",
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  "author_email": "coenen@ipi.uni-hannover.de",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/0078519",
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  "doi": "10.25835/0078519",
            
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  "doi_date_published": "2020-07-14",
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  "doi_date_published": "2020-07-14",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
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  "domain": "https://data.uni-hannover.de",
            
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  "groups": [],
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  "groups": [],
            
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  "have_copyright": "Yes",
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  "have_copyright": "Yes",
            
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  "id": "df2eb5a1-e09f-422d-9dec-537f10d18a2a",
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  "id": "df2eb5a1-e09f-422d-9dec-537f10d18a2a",
            
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  "isopen": false,
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  "isopen": false,
            
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  "license_id": "CC-BY-NC-3.0",
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  "license_id": "CC-BY-NC-3.0",
            
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  "license_title": "CC-BY-NC-3.0",
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  "license_title": "CC-BY-NC-3.0",
            
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  "maintainer": "Max Coenen",
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  "maintainer": "Max Coenen",
            
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  "maintainer_email": "",
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  "maintainer_email": "",
            
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  "metadata_created": "2021-10-14T10:15:59.217275",
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  "metadata_created": "2021-10-14T10:15:59.217275",
            
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  "metadata_modified": "2023-01-12T13:14:16.154143",
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  "metadata_modified": "2023-08-04T08:46:33.167417",
            
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  "name": "luh-icsens-stereo-image-vehicle-dataset",
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  "name": "luh-icsens-stereo-image-vehicle-dataset",
            
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  "notes": "The _i.c.sens Stereo Image Vehicle Dataset_ is a dataset 
21
  "notes": "The _i.c.sens Stereo Image Vehicle Dataset_ is a dataset 
            
22
for vehicle detection, pose estimation, and reconstruction. It 
22
for vehicle detection, pose estimation, and reconstruction. It 
            
23
consists of street-level stereo images and delivers reference 
23
consists of street-level stereo images and delivers reference 
            
24
information for the 3D pose and shape of vehicles being visible in the 
24
information for the 3D pose and shape of vehicles being visible in the 
            
25
scene. For the acquisition of the data, a vehicle was equipped with a 
25
scene. For the acquisition of the data, a vehicle was equipped with a 
            
26
synchronised and calibrated stereo camera rig and stereoscopic image 
26
synchronised and calibrated stereo camera rig and stereoscopic image 
            
27
sequences were recorded in urban environments in the city of Hanover 
27
sequences were recorded in urban environments in the city of Hanover 
            
28
for the generation of the data set. Vehicle CAD models are manually 
28
for the generation of the data set. Vehicle CAD models are manually 
            
29
fitted to the observations and are provided as reference data. 
29
fitted to the observations and are provided as reference data. 
            
30
\r\n\r\nExamples of the reference CAD models can be seen in the 
30
\r\n\r\nExamples of the reference CAD models can be seen in the 
            
31
subsequent figure:\r\n![Reference CAD 
31
subsequent figure:\r\n![Reference CAD 
            
32
ource/43941f67-663f-42ff-b604-298faa0ba754/download/labelsexamples.png 
32
ource/43941f67-663f-42ff-b604-298faa0ba754/download/labelsexamples.png 
            
33
\"Visualisation of the reference CAD models\")\r\n\r\n\r\nDetails on 
33
\"Visualisation of the reference CAD models\")\r\n\r\n\r\nDetails on 
            
34
the data and its usage can be found in the provided __documentation__ 
34
the data and its usage can be found in the provided __documentation__ 
            
35
file.\r\n\r\n# __Related Publications:__\r\n* __Coenen, M. and 
35
file.\r\n\r\n# __Related Publications:__\r\n* __Coenen, M. and 
            
36
Rottensteiner, F., 2019__: Probabilistic Vehicle Reconstruction Using 
36
Rottensteiner, F., 2019__: Probabilistic Vehicle Reconstruction Using 
            
37
a Multi-Task\r\nCNN. In: _IEEE International Conference on Computer 
37
a Multi-Task\r\nCNN. In: _IEEE International Conference on Computer 
            
38
Vision Workshops (ICCV Workshops)_,\r\npp. 
38
Vision Workshops (ICCV Workshops)_,\r\npp. 
            
39
822-831.\r\nhttps://ieeexplore.ieee.org/document/9022056\r\n\r\n* 
39
822-831.\r\nhttps://ieeexplore.ieee.org/document/9022056\r\n\r\n* 
            
40
__Sch\u00f6n, S., Brenner, C., Alkhatib, H., Coenen, M., Dbouk, H., 
40
__Sch\u00f6n, S., Brenner, C., Alkhatib, H., Coenen, M., Dbouk, H., 
            
41
Garcia-Fernandez, N., Fischer, C.,\r\nHeipke, C., Lohmann, K., 
41
Garcia-Fernandez, N., Fischer, C.,\r\nHeipke, C., Lohmann, K., 
            
42
Neumann, I., Nguyen, U., Paffenholz, J.-A., Peters, T., 
42
Neumann, I., Nguyen, U., Paffenholz, J.-A., Peters, T., 
            
43
Rottensteiner,\r\nF., Schachtschneider, J., Sester, M., Sun, L., 
43
Rottensteiner,\r\nF., Schachtschneider, J., Sester, M., Sun, L., 
            
44
Vogel, S., Voges, R. and Wagner, B., 2018:__ Integrity\r\nand 
44
Vogel, S., Voges, R. and Wagner, B., 2018:__ Integrity\r\nand 
            
45
Collaboration in Dynamic Sensor Networks. _Sensors_ 18(7), pp. 
45
Collaboration in Dynamic Sensor Networks. _Sensors_ 18(7), pp. 
            
46
2400-2421.\r\nhttps://www.mdpi.com/1424-8220/18/7/2400",
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2400-2421.\r\nhttps://www.mdpi.com/1424-8220/18/7/2400",
            
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  "num_resources": 8,
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  "num_tags": 4,
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2021-10-14T10:15:59.145624",
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    "created": "2021-10-14T10:15:59.145624",
            
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    "description": "Graduiertenkolleg 2159 
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    "description": "Graduiertenkolleg 2159 
            
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\r\nhttps://www.icsens.uni-hannover.de/",
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\r\nhttps://www.icsens.uni-hannover.de/",
            
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ni-hannover.de/fileadmin/site-templates/logos/icsens/ICSENS_logo.png",
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ni-hannover.de/fileadmin/site-templates/logos/icsens/ICSENS_logo.png",
            
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  "relationships_as_subject": [],
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  "relationships_as_subject": [],
            
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  "repository_name": "Leibniz University Hannover",
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  "repository_name": "Leibniz University Hannover",
            
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      "created": "2020-06-15T15:23:26.240949",
            
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      "description": "Demo code for the usage of the reference 
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      "description": "Demo code for the usage of the reference 
            
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labels",
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labels",
            
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      "description": "Reference labels for the vehicle detection, pose 
            
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and shape",
            
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