RealisDance-DiT: Simple yet Strong Baseline towards Controllable Character Animation in the Wild

This repository is the test dataset proposed in RealisDance-DiT, called RealisDance-Val. RealisDance-Val is collected to evaluate controllable character animation in the wild.

  Note

Just for your information, we publish the poses we used for testing, which may not be completely accurate. If you wish, you can extract your own motion representations from the gt videos.… See the full description on the dataset page: https://huggingface.co/datasets/theFoxofSky/RealisDance-Val.

Context

Dataset of impact craters on the Moon derived by LU3M6TGT global catalog. It was created by a deep learning model YOLOLens, which also increases the spatial image resolution allowing crater detection down to sizes as small as 0.5 km. The full database encompasses more than 3.5 million craters, a value three times larger with respect to other lunar catalogues currently available, and this release represents a YOLO format version of a subset of LU3M6TGT catalog useful to train the deep learning model in easy way.

Content

• The dataset is created by YOLOLens model (see Reference) using the sources of the Lunar Reconnaissance Orbiter Camera (LROC).
• Splitted into Train/val test (1545 val img and 8756 train img), 3x416x416 of shape, 0-255 bit depth.
• YOLO format release of a subset of LU3M6TGT catalog (The full catalog in format science (coordinates system) can be found (see LU5M812TGT dataset). soon after journal publication at Zenodo repository).
• The Global Mosaic Map used as main data source can be found in the following link: https://astrogeology.usgs.gov/search?pmi-target=moon under the name: Moon LRO LROC WAC Global Morphology Mosaic 100m v3.
• The resulting dataset images & labels are converted using the orthographic projection useful to avoid dilatation images due to the main mosaic map given into the cylindrical projection.

Technical details: 1. Change the absolute path inside the data.yaml file. 2. At first use delete labels.cache inside the val folder (if you'll use yolo model it will create for you again using your new absolute path). 3. The dilatation offsets contains the shifting in x-axis for each image row due to the projection changing. You can ignore this folder.

BibTeX Citation

If you use the dataset in a scientific publication, I would appreciate using the following citation:

@article{la2023yololens, title={YOLOLens: A Deep Learning Model Based on Super-Resolution to Enhance the Crater Detection of the Planetary Surfaces}, author={La Grassa, Riccardo and Cremonese, Gabriele and Gallo, Ignazio and Re, Cristina and Martellato, Elena}, journal={Remote Sensing}, volume={15}, number={5}, pages={1171}, year={2023}, publisher={MDPI} }

Contact email: riccardo.lagrassa@inaf.it

Scope of studies established according to articles L111-7 to L111-10 of the urban planning code. Here are the boundaries of studies agreed and planned located within the Operation d’Inêt National (OIN) Orly-Rungis Seine-Amont.

New structured layer for Ile-de-France and used regionally in the regional planning database (Badora)

Perimeters and elus of the cantons of the Val d’Oise

Bradley/fineweb-sample-100BT_over-2048-tokens-subset-split-processed-val dataset hosted on Hugging Face and contributed by the HF Datasets community

🇫🇷 프랑스

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This EarthCARE collection is restricted, and contains the following data products:

· Level 1b: Fully Calibrated and Geolocated Instrument Science Measurements

Level 1b data represents the fully processed, calibrated, and geolocated measurements from EarthCARE's instruments. Each measurement is aligned with the native instrument grid. For the Broadband Radiometer (BBR), measurements are also spatially integrated to various groundpixel sizes.

· Level 1c (MSI only): MSI Level 1b Data Interpolated to a Common Spatial Grid

Specifically for the Multi-Spectral Imager (MSI), Level 1c data involves interpolating Level 1b measurements onto a standardized spatial grid that is consistent across all MSI bands. This grid closely matches the spacing used in MSI Level 1b data.

· Level 1d: Joint Standard Grid (JSG) for All Instruments with ECMWF Meteorological Fields.

Level 1d data provides a spatial grid to enable easy collocation and synergistic use of the data from all EarthCARE instruments, named the "joint standard grid." Additionally, this level incorporates ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological fields limited to the EarthCARE swath, enabling comprehensive analysis and modeling of atmospheric conditions within the satellite's coverage area.

In conjunction with the referendum on Swedish membership of the European monetary Union (EMU) an election study was carried out in collaboration between Statistics Sweden and the Department of Political Science at Göteborg University. Purpose: Explain why people vote as they do and why an election ends in a particular way. Track and follow trends in the Swedish electoral democracy and make comparisons with other countries. In conjunction with the referendum on Swedish membership of the European monetary Union (EMU) an election study was carried out in collaboration between Statistics Sweden and the Department of Political Science at Göteborg University. Syfte: Förklara varför väljare röstar som de gör och varför val slutar som de gör. Spåra och följa trender i svensk valdemokrati och göra jämförelser med utvecklingen i andra länder. Probability: Simple random Sannolikhetsurval: obundet slumpmässigt urval Probability Sannolikhetsurval Elections Government International polit... Internationell poli... POLITICS POLITIK Political Science Political behaviour... Politiska beteenden... Regering Samhällsvetenskap Social Sciences Statsvetenskap Val currencies economics ekonomi elections electoral issues european integration european monetary s... european union europeisk integration europeiska monetära... europeiska unionen finance finans folkomröstningar gemensam europeisk ... integration international econo... international monet... internationell ekonomi internationellt val... monetary economics monetär ekonomi political institutions political systems a... political unification politics politik politisk likriktning politiska instituti... politiska system oc... referendums single european cur... val valfrågor valuta

Public Utilities can be classified into four categories according to their objectives:* heritage conservation easements;* easements relating to the use of certain resources and equipment;* easements relating to National Defence; and* easements relating to public safety and health. This data standard provides a technical framework describing in detail how to dematerialise these easements into a spatial database that can be used by a GIS tool and interoperable for separate territories. The scope of this standard of data includes the concepts of easements: the legal acts establishing them, the managers, the generators and the bases. At the same time in the development of this COVADIS data standard, a working group was held under the aegis of the DGALN whose aim was to produce methodological sheets describing the legal bases and geomatics aspects of each category of easement. These sheets complete with a more detailed business description of each easement the present standard and are online on the PND Urbanism website. This COVADIS standard was developed using the standard SUP categories and the 2007 CNIG SUP model. This standard follows and complements the one on PLUs validated in 2010. This data standard is now to be used within MEDDTL and MAAPRAT to store, exploit and exchange data from the dematerialisation of SUPs.

Crystals of Boc-γ4(R)Val-Val-OH undergo a reversible first-order single crystal to single crystal phase transition at Tc ≈ 205 K from the orthorhombic space group P22121 (Z′ = 1) to the monoclinic space group P21 (Z′ = 2) with a hysteresis of ∼2.1 K. The low-temperature monoclinic form is best described as a nonmerohedral twin with ∼50% contributions from its two components. The thermal behavior of the dipeptide crystals was characterized by differential scanning calorimetry experiments. Visual changes in birefringence of the sample during heating and cooling cycles on a hot-stage microscope with polarized light supported the phase transition. Variable-temperature unit cell check measurements from 300 to 100 K showed discontinuity in the volume and cell parameters near the transition temperature, supporting the first-order behavior. A detailed comparison of the room-temperature orthorhombic form with the low-temperature (100 K) monoclinic form revealed that the strong hydrogen-bonding motif is retained in both crystal systems, whereas the non-covalent interactions involving side chains of the dipeptide differ significantly, leading to a small change in molecular conformation in the monoclinic form as well as a small reorientation of the molecules along the ac plane. A rigid-body thermal motion analysis (translation, libration, screw; correlation of translation and libration) was performed to study the crystal entropy. The reversible nature of the phase transition is probably the result of an interplay between enthalpy and entropy: the low-temperature monoclinic form is enthalpically favored, whereas the room-temperature orthorhombic form is entropically favored.

Germany MOI: EU: Val: Mfg: Basic Metals (BM) data was reported at 103.400 2010=100 in Dec 2017. This records a decrease from the previous number of 111.700 2010=100 for Nov 2017. Germany MOI: EU: Val: Mfg: Basic Metals (BM) data is updated monthly, averaging 98.150 2010=100 from Jan 2003 (Median) to Dec 2017, with 180 observations. The data reached an all-time high of 144.100 2010=100 in May 2008 and a record low of 41.600 2010=100 in Aug 2003. Germany MOI: EU: Val: Mfg: Basic Metals (BM) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.C032: Manufacturing Orders Received Index: 2010=100: Value: Foreign. Rebased from 2010=100 to 2015=100 Replacement series ID: 401105827

Service diffusant la carte piézométrique du Val d'Orléans - calcaires - basses eaux - sept-oct 1966

Germany MOPI: swda: FO: Val: Mfg: Basic Metals (BM) data was reported at 131.300 2005=100 in Dec 2012. This records an increase from the previous number of 122.900 2005=100 for Nov 2012. Germany MOPI: swda: FO: Val: Mfg: Basic Metals (BM) data is updated monthly, averaging 73.350 2005=100 from Jan 1991 (Median) to Dec 2012, with 264 observations. The data reached an all-time high of 154.800 2005=100 in May 2008 and a record low of 41.800 2005=100 in Jan 1993. Germany MOPI: swda: FO: Val: Mfg: Basic Metals (BM) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.B023: Manufacturing Output Index: 2005=100: Seasonally and Working Day Adjusted.

This study is number six in the collection of Swedish election studies carried out in connection with a general election. In 1973 a new kind of panel was introduced. This was a two-run panel, in which half of the 1973 sample was reinterviewed in 1976. The new respondents in 1976 were reinterviewed in 1979, and so on. In this way, all respondents will be interviewed twice. In addition to the usual content, this study includes a large number of questions on international politics and events; interest in international politics, opinions on alarming international events, the superpowers, the Common Market, the Middle East conflict, and the war in Vietnam. There are also questions on what the respondent wants the parties to accomplish on national and local level, and about the respondent´s knowledge of the candidates to the parliamentary and local election. Unlike most of the election studies, this study does not include questions on mass media. Purpose: Explain why people vote as they do and why an election ends in a particular way. Track and follow trends in the Swedish electoral democracy and make comparisons with other countries. This study is number six in the collection of Swedish election studies carried out in connection with a general election. In 1973 a new kind of panel was introduced. This was a two-run panel, in which half of the 1973 sample was reinterviewed in 1976. The new respondents in 1976 were reinterviewed in 1979, and so on. In this way, all respondents will be interviewed twice. In addition to the usual content, this study includes a large number of questions on international politics and events; interest in international politics, opinions on alarming international events, the superpowers, the Common Market, the Middle East conflict, and the war in Vietnam. There are also questions on what the respondent wants the parties to accomplish on national and local level, and about the respondent´s knowledge of the candidates to the parliamentary and local election. Unlike most of the election studies, this study does not include questions on mass media. Syfte: Förklara varför väljare röstar som de gör och varför val slutar som de gör. Spåra och följa trender i svensk valdemokrati och göra jämförelser med utvecklingen i andra länder. I 1973 års undersökning tillämpades en annan metod för urvalsdragning än vid de tidigare undersökningarna. Den tidigare användningen av SCB:s sk basurval ersattes med en urvalsdragning i ett steg, direkt från SCB:s register över totalbefolkningen (RTB), med hjälp av SCB:s standardprogram för slumpmässiga urval. Vid urvalsdragningen bortsorterades personer som på grund av rösträttshinder ej ingick i målpopulationen. I målpopulationen ingår även röstberättigade utlandssvenskar. Dessa ingår emellertid ej i urvalsramen.I 1973 års undersökning tillämpades en annan metod för urvalsdragning än vid de tidigare undersökningarna. Den tidigare användningen av SCB:s sk basurval ersattes med en urvalsdragning i ett steg, direkt från SCB:s register över totalbefolkningen (RTB), med hjälp av SCB:s standardprogram för slumpmässiga urval. Vid urvalsdragningen bortsorterades personer som på grund av rösträttshinder ej ingick i målpopulationen. I målpopulationen ingår även röstberättigade utlandssvenskar. Dessa ingår emellertid ej i urvalsramen.

Germany MOPI: DO: Val: Mfg: Basic Metals (BM) data was reported at 88.100 2005=100 in Dec 2012. This records a decrease from the previous number of 135.600 2005=100 for Nov 2012. Germany MOPI: DO: Val: Mfg: Basic Metals (BM) data is updated monthly, averaging 82.250 2005=100 from Jan 1991 (Median) to Dec 2012, with 264 observations. The data reached an all-time high of 165.800 2005=100 in Jun 2008 and a record low of 50.900 2005=100 in Dec 1996. Germany MOPI: DO: Val: Mfg: Basic Metals (BM) data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.B022: Manufacturing Output Index: 2005=100.

Germany MOI: DO: Val: Mfg: PH: Basic data was reported at 175.300 2005=100 in Dec 2012. This records a decrease from the previous number of 203.500 2005=100 for Nov 2012. Germany MOI: DO: Val: Mfg: PH: Basic data is updated monthly, averaging 100.150 2005=100 from Jan 1991 (Median) to Dec 2012, with 264 observations. The data reached an all-time high of 312.700 2005=100 in Sep 2011 and a record low of 57.700 2005=100 in Feb 1993. Germany MOI: DO: Val: Mfg: PH: Basic data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.C043: Manufacturing Orders Received Index: 2005=100: Value.

Germany MOPI: swda: DO: Val: Mfg: Basic Metals data was reported at 112.900 2015=100 in May 2018. This records an increase from the previous number of 111.700 2015=100 for Apr 2018. Germany MOPI: swda: DO: Val: Mfg: Basic Metals data is updated monthly, averaging 75.500 2015=100 from Jan 1991 (Median) to May 2018, with 329 observations. The data reached an all-time high of 133.600 2015=100 in Jun 2008 and a record low of 53.200 2015=100 in May 1993. Germany MOPI: swda: DO: Val: Mfg: Basic Metals data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.B022: Manufacturing Output Index: 2015=100: Seasonally and Working Day Adjusted.