dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
Argoverse 2 | Argoverse 2 (AV2) is a collection of three datasets for perception and forecasting research in the self-driving domain. The annotated Sensor Dataset contains 1,000 sequences of multimodal data, encompassing high-resolution imagery from seven ring cameras, and two stereo cameras in addition to lidar point clouds, and 6-... | Provide a detailed description of the following dataset: Argoverse 2 |
MiSCS | Microscopy images of shrub cross sections for instance segmentation of tree rings.
Tree rings are used in dendroecology to reconstruct past climate. Shrubs are of special importance for climate reconstruction in the Arctic as they are the only plants with tree rings that can grow there. From a computer vision point ... | Provide a detailed description of the following dataset: MiSCS |
ChatGPT Paraphrases | This is a dataset of paraphrases created by ChatGPT.
**We used this prompt to generate paraphrases:**
Generate 5 similar paraphrases for this question, show it like a numbered list without commentaries: *{text}*
This dataset is based on the [Quora paraphrase question](https://www.kaggle.... | Provide a detailed description of the following dataset: ChatGPT Paraphrases |
BUAA-MIHR dataset | BUAA-MIHR dataset is a remote photoplethysmography (rPPG) dataset. BUAA-MIHR dataset for evaluation of remote photoplethysmography pipeline under multi-illumination situations. We recruited 15 healthy subjects (12 male, 3 female, 18 to 30 years old) in this experiment and a total number of 165 video sequences were reco... | Provide a detailed description of the following dataset: BUAA-MIHR dataset |
AISIA-VN-Review-S | In AISIA-VN-Review-S and AISIA-VN-Review-F datasets, we first collect 450K customer reviewing comments from various e–commerce websites. Then, we manually label each review to be either positive or negative, resulting in 358,743 positive reviews and 100,699 negative reviews. We named this dataset the sentiment classifi... | Provide a detailed description of the following dataset: AISIA-VN-Review-S |
6IMPOSE | The dataset includes the synthetic data generated from rendering the 3D meshes of LM objects and several household objects in Blender for training 6D pose estimation algorithms. The whole dataset contains synthetic data for 18 objects (13 from LM and 5 from household objects), with 20,000 data samples for each object. ... | Provide a detailed description of the following dataset: 6IMPOSE |
LEA-GCN-dataset | The datasets of "Towards Lightweight Cross-domain Sequential Recommendation via External Attention-enhanced Graph Convolution Network" (DASFAA 2023) | Provide a detailed description of the following dataset: LEA-GCN-dataset |
OntoLAMA | Instructions: <https://krr-oxford.github.io/DeepOnto/ontolama/>.
Huggingface: <https://huggingface.co/datasets/krr-oxford/OntoLAMA>.
Zenodo: <https://doi.org/10.5281/zenodo.6480540 > | Provide a detailed description of the following dataset: OntoLAMA |
Bio-ML | The Bio-ML dataset provides five ontology pairs for both equivalence and subsumption ontology matching.
See detailed instructions at: [https://krr-oxford.github.io/DeepOnto/bio-ml](https://krr-oxford.github.io/DeepOnto/bio-ml)
See the OAEI Bio-ML track at: [https://www.cs.ox.ac.uk/isg/projects/ConCur/oaei/](http... | Provide a detailed description of the following dataset: Bio-ML |
GIRT-Data | GIRT-Data is the first and largest dataset of issue report templates (IRTs) in both YAML and Markdown format. This dataset and its corresponding open-source crawler tool are intended to support research in this area and to encourage more developers to use IRTs in their repositories. The stable version of the dataset co... | Provide a detailed description of the following dataset: GIRT-Data |
SynthBRSet | 3D Computer Graphics is leveraged to generate a large and diverse dataset for training bike rotation estimators in bike parking assessment. By using 3D graphics software (Blender), the algorithm is able to accurately annotate the rotations of bikes with respect to the parking spot area in two axes y and z , which is cr... | Provide a detailed description of the following dataset: SynthBRSet |
MFNet | The first RGB-Thermal urban scene image dataset with pixel-level annotation. We published this new RGB-Thermal semantic segmentation dataset in support of further development of autonomous vehicles in the future. This dataset contains 1569 images (820 taken at daytime and 749 taken at nighttime). Eight classes of obsta... | Provide a detailed description of the following dataset: MFNet |
Chicago Face Database (CFD) | "The Chicago Face Database was developed at the University of Chicago by Debbie S. Ma, Joshua Correll, and Bernd Wittenbrink. The CFD is intended for use in scientific research. It provides high-resolution, standardized photographs of male and female faces of varying ethnicity between the ages of 17-65. Extensive normi... | Provide a detailed description of the following dataset: Chicago Face Database (CFD) |
ViNLI | A large-scale and high-quality corpus is necessary for studies on NLI for Vietnamese, which can be considered a low-resource language. In this paper, we introduce ViNLI (Vietnamese Natural Language Inference), an open-domain and high-quality corpus for evaluating Vietnamese NLI models, which is created and evaluated wi... | Provide a detailed description of the following dataset: ViNLI |
OpenLane-V2 val | **OpenLane-V2** is the world's first perception and reasoning benchmark for scene structure in autonomous driving. The primary task of the dataset is scene structure perception and reasoning, which requires the model to recognize the dynamic drivable states of lanes in the surrounding environment. The challenge of this... | Provide a detailed description of the following dataset: OpenLane-V2 val |
METABRIC | https://ega-archive.org/studies/EGAS00000000083 | Provide a detailed description of the following dataset: METABRIC |
SLOPER4D | **SLOPER4D** is a novel scene-aware dataset collected in large urban environments to facilitate the research of global human pose estimation (GHPE) with human-scene interaction in the wild. It consists of 15 sequences of human motions, each of which has a trajectory length of more than 200 meters (up to 1,300 meters) a... | Provide a detailed description of the following dataset: SLOPER4D |
YTD-18M | YTD-18M is a large-scale corpus of 18M video-based dialogues, constructed from web videos: crucial to the data collection pipeline is a pretrained language model that converts error-prone automatic transcripts to a cleaner dialogue format while maintaining meaning. | Provide a detailed description of the following dataset: YTD-18M |
Overall-Driving-Behavior-Recognition-By-Smartphone | Monitoring and evaluating of driving behavior is the main goal of this paper that encourage us to develop a new system based on Inertial Measurement Unit (IMU) sensors of smartphones. In this system, a hybrid of Discrete Wavelet Transformation (DWT) and Adaptive Neuro Fuzzy Inference System (ANFIS) is used to recognize... | Provide a detailed description of the following dataset: Overall-Driving-Behavior-Recognition-By-Smartphone |
Microscopy Images of Drosophila Wing | Microscopy Images of the Drosophila Wing dataset are divided into two folders, Tumor/ No Tumor. The tumor folder has images of different stages of cancer, including both early and late stages. The organization of images was done in a way that the Tumor Folder has images that already have a Tumor or is going to develop ... | Provide a detailed description of the following dataset: Microscopy Images of Drosophila Wing |
16s rDNA sequencing of feces from C9orf72 loss of function mice | In one round of sequencing, 5 fecal pellets from 2 pro-inflammatory environments (Harvard BRI/Johns Hopkins) and 2 pro-survival environments (Broad Institute/Jackson Labs) were sequenced at the 16s rDNA locus. In a second round of sequencing, 9 fecal pellets from Harvard BRI, 9 fecal pellets from Broad Institute, 6 fec... | Provide a detailed description of the following dataset: 16s rDNA sequencing of feces from C9orf72 loss of function mice |
CTCyclistDetectionDataset | Over 20,000 annotated synthetic images and web-scraped images of bicyclists with bounding box annotations in Pascal VOC format. | Provide a detailed description of the following dataset: CTCyclistDetectionDataset |
nuScenes LiDAR only | Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image based benchmark datasets have driven development in computer vision tasks such as object detection, tracking and segmentation of agents in the environment. Most autonomous vehicles, however, carry a combinatio... | Provide a detailed description of the following dataset: nuScenes LiDAR only |
GAS | **GAS (Grasp Area Segmentation)** dataset consists of 10089 RGB images of cluttered scenes grouped into 1121 grasp-area segmentation tasks. For each RGB image we provide a binary segmentation map with the graspable and non-graspable regions for every object in the scene. The dataset can be used for meta-training part-b... | Provide a detailed description of the following dataset: GAS |
CIMAT-Cyclist | This provides a benchmark for cyclist's orientation detection, "CIMAT-Cyclist" with bounding box based labels according to eight different classes depending on the orientation. Which contains 11, 103 images, of which 6,605 images were collected in approximately 450 videos and images taken from sports events and the str... | Provide a detailed description of the following dataset: CIMAT-Cyclist |
Caselaw4 | __Caselaw4__ is a dataset of 350k common law judicial decisions from the [U.S. Caselaw Access Project](https://case.law/), of which 250k have been automatically annotated with binary outcome labels of _AFFIRM_ and _REVERSE_.
The court case reports used in the dataset are from New Mexico, North Carolina, Illinois, ... | Provide a detailed description of the following dataset: Caselaw4 |
BFN | This database is a database of backdoored neural networks intended for face recognition. The networks are of the FaceNet architecture and are trained on Casia-WebFace, with and without additional samples (which are the source of the backdoor). More information regarding backdoors and the project within which this fits ... | Provide a detailed description of the following dataset: BFN |
DarkTrack2021 | **DarkTrack2021** is a challenging nighttime UAV tracking benchmark, which contains 110 challenging sequences with over 100 K frames in total. | Provide a detailed description of the following dataset: DarkTrack2021 |
RarePlanes | RarePlanes is a unique open-source machine learning dataset from CosmiQ Works and AI.Reverie that incorporates both real and synthetically generated satellite imagery. The RarePlanes dataset specifically focuses on the value of AI.Reverie synthetic data to aid computer vision algorithms in their ability to automaticall... | Provide a detailed description of the following dataset: RarePlanes |
ICVL-HSI | ICVL is a hyperspectral image dataset, collected by "Sparse Recovery of Hyperspectral Signal from Natural RGB Images"
The database images were acquired using a Specim PS Kappa DX4 hyperspectral camera and a rotary stage for spatial scanning. At this time it contains 200 images and will continue to grow progressively... | Provide a detailed description of the following dataset: ICVL-HSI |
MVK | The dataset contains single-shot videos taken from moving cameras in underwater environments. The first shard of a new Marine Video Kit dataset is presented to serve for video retrieval and other computer vision challenges. In addition to basic meta-data statistics, we present several insights based on low-level featur... | Provide a detailed description of the following dataset: MVK |
DocRED-FE | DocRED-FE is the DocRED with Fine-Grained Entity Type | Provide a detailed description of the following dataset: DocRED-FE |
IBL-NeRF | IBL-NeRF Dataset.
Contains multi-view images with its intrinsic components. | Provide a detailed description of the following dataset: IBL-NeRF |
Biwi 3D Audiovisual Corpus of Affective Communication - B3D(AC)^2 | **BIWI 3D** corpus comprises a total of 1109 sentences uttered by 14 native English speakers (6 males and 8 females). A real time 3D scanner and a professional microphone were used to capture the facial movements and the speech of the speakers. The dense dynamic face scans were acquired at 25 frames per second and the ... | Provide a detailed description of the following dataset: Biwi 3D Audiovisual Corpus of Affective Communication - B3D(AC)^2 |
Brightfield vs Fluorescent Staining Dataset | Differential fluorescent staining is an effective tool widely adopted for the visualization, segmentation and quantification of cells and cellular substructures as a part of standard microscopic imaging protocols. Incompatibility of staining agents with viable cells represents major and often inevitable limitations to ... | Provide a detailed description of the following dataset: Brightfield vs Fluorescent Staining Dataset |
OmniBlender | Synthetic omnidirectional multi-view image dataset.
Photo-realistic rendered images with Cycles engine. | Provide a detailed description of the following dataset: OmniBlender |
Ricoh360 | Real-world omnidirectional multi-view image dataset. | Provide a detailed description of the following dataset: Ricoh360 |
Burned Area Delineation from Satellite Imagery | The dataset contains 73 satellite images of different forests damaged by wildfires across Europe with a resolution of up to 10m per pixel. Data were collected from the Sentinel-2 L2A satellite mission and the target labels were generated from the Copernicus Emergency Management Service (EMS) annotations, with five diff... | Provide a detailed description of the following dataset: Burned Area Delineation from Satellite Imagery |
ShapeIt | The ShapeIt dataset introduced by Alper et al. (2023) consists of 109 nouns and noun phrases along with the basic shape normally associated with that item, chosen from the set {circle, rectangle, triangle}. | Provide a detailed description of the following dataset: ShapeIt |
Video Call MOS Set | The dataset contains 10 reference videos and 1467 degraded videos. The videos were transmitted via Microsoft Teams calls in 83 different network conditions and contain various typical videoconferencing impairments. It also includes P.910 Crowd subjective video MOS ratings (see paper for more info). | Provide a detailed description of the following dataset: Video Call MOS Set |
PAIR-LRT-Human Dataset | **PAIR-LRT-Human Dataset** contains pairs of thermal and RGB images captured using a FLIR Lepton3.5 thermal sensor and a Raspberry Pi camera v2, respectively. The dataset includes a total of 33,228 image pairs captured under different environmental conditions, with one human occupant in a standing position and an upper... | Provide a detailed description of the following dataset: PAIR-LRT-Human Dataset |
Mocheg | A large-scale dataset that consists of 21,184 claims, where each claim is assigned a truthfulness label and ruling statement, with 58,523 pieces of evidence in the form of text and images. It supports the end-to-end multimodal fact-checking and explanation generation, where the input is a claim and a large collection o... | Provide a detailed description of the following dataset: Mocheg |
Guzheng_Tech99 | Instrument playing technique (IPT) is a key element of musical presentation.
Guzheng is a polyphonic instrument. In Guzheng performance, notes with different IPTs are usually overlapped and mixed IPTs that can be decomposed into multiple independent IPTs are usually used. Most existing work on IPT detection typicall... | Provide a detailed description of the following dataset: Guzheng_Tech99 |
ESP Dataset | ESP dataset (Evaluation for Styled Prompt dataset) is a new benchmark for zero-shot domain-conditional caption generation. The dataset aims to evaluate the capability to generate diverse domain-specific language conditioned on the same image. It comprises 4.8k captions from 1k images in the COCO Captions test set. We c... | Provide a detailed description of the following dataset: ESP Dataset |
CVACT | The CVACT dataset is a matching task between street- and aerial views, from Canberra (Australia). This task helps to determine localization without GPS coordinates for the street-view images. Google Street View panoramas are used as ground images, and matching aerial images also from the Google Maps API. The dataset co... | Provide a detailed description of the following dataset: CVACT |
VIGOR | Similar to CVUSA and CVACT, the VIGOR dataset contains satellites and street imagery to match them to each other to find the location of the street imagery. For this purpose, data from 4 major American cities were used, namely San Francisco, New York, Seattle and Chicago. Unlike the previous datasets, there are two set... | Provide a detailed description of the following dataset: VIGOR |
CIFAKE: Real and AI-Generated Synthetic Images | The quality of AI-generated images has rapidly increased, leading to concerns of authenticity and trustworthiness.
CIFAKE is a dataset that contains 60,000 synthetically-generated images and 60,000 real images (collected from CIFAR-10). Can computer vision techniques be used to detect when an image is real or has be... | Provide a detailed description of the following dataset: CIFAKE: Real and AI-Generated Synthetic Images |
WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images | WHOOPS! Is a dataset and benchmark for visual commonsense. The dataset is comprised of purposefully commonsense-defying images created by designers using publicly-available image generation tools like Midjourney. It contains commonsense-defying image from a wide range of reasons, deviations from expected social norms a... | Provide a detailed description of the following dataset: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images |
MBPP | The benchmark consists of around 1,000 crowd-sourced Python programming problems, designed to be solvable by entry-level programmers, covering programming fundamentals, standard library functionality, and so on. Each problem consists of a task description, code solution and 3 automated test cases. | Provide a detailed description of the following dataset: MBPP |
OPRA | The OPRA Dataset was introduced in Demo2Vec: Reasoning Object Affordances From Online Videos (CVPR'18) for reasoning object affordances from online demonstration videos. It contains 11,505 demonstration clips and 2,512 object images scraped from 6 popular YouTube product review channels along with the corresponding aff... | Provide a detailed description of the following dataset: OPRA |
EPIC-Hotspot | From Grounded Human-Object Interaction Hotspots from Video (ICCV'19): We collect annotations for interaction keypoints on EPIC Kitchens in order to quantitatively evaluate our method in parallel to the OPRA dataset (where annotations are available). We note that these annotations are collected purely for evaluation, an... | Provide a detailed description of the following dataset: EPIC-Hotspot |
Autoregressive Paraphrase Dataset (ARPD) | For more details see https://huggingface.co/datasets/jpwahle/autoregressive-paraphrase-dataset | Provide a detailed description of the following dataset: Autoregressive Paraphrase Dataset (ARPD) |
Ranking social media news feed | A dataset consisting of recipient 46 users and, 26180 tweets. The dataset includes the news feed of the users and 13 features that may influence the relevance of the tweets. | Provide a detailed description of the following dataset: Ranking social media news feed |
N5k360 | We applied our framework, dubbed as ”PreNeRF 360”, to enable the use of the Nutrition5k dataset in NeRF and introduce an updated version of this dataset, known as the N5k360 dataset. | Provide a detailed description of the following dataset: N5k360 |
NIH-CXR-LT | NIH-CXR-LT. NIH ChestXRay14 contains over 100,000 chest X-rays labeled with 14 pathologies, plus a “No Findings” class. We construct a single-label, long-tailed version of the NIH ChestXRay14 dataset by introducing five new disease findings described above. The resulting NIH-CXR-LT dataset has 20 classes, including 7 h... | Provide a detailed description of the following dataset: NIH-CXR-LT |
MIMIC-CXR-LT | MIMIC-CXR-LT. We construct a single-label, long-tailed version of MIMIC-CXR in a similar manner. MIMIC-CXR is a multi-label classification dataset with over 200,000 chest X-rays labeled with 13 pathologies and a “No Findings” class. The resulting MIMIC-CXR-LT dataset contains 19 classes, of which 10 are head classes, 6... | Provide a detailed description of the following dataset: MIMIC-CXR-LT |
GATITOS | The GATITOS (Google's Additional Translations Into Tail-languages: Often Short) dataset is a high-quality, multi-way parallel dataset of tokens and short phrases, intended for training and improving machine translation models. This dataset consists in 4,000 English segments (4,500 tokens) that have been translated into... | Provide a detailed description of the following dataset: GATITOS |
ALPIX-VSR | we collected a new real-world dataset, called ALPIXVSR, using a ALPIX-Eiger event camera1
. The camera outputs well aligned RGB frames and events. The RGB frames
enjoy a resolution of 3264 × 2448 and are generated by a
carefully designed image signal processor(ISP) from RAW
data with the Quad Bayer pattern , and th... | Provide a detailed description of the following dataset: ALPIX-VSR |
EHE | Human Action Evaluation (HAE) has rarely been applied to real-world disease monitoring, the EHE dataset aims to gather sample data to validate effective HAE methods that could then be expanded on a larger validation scale. EHE consists of several actions from morning exercises that patients complete daily in the elderl... | Provide a detailed description of the following dataset: EHE |
BEAR | **BEAR (Benchmark on video Action Recognition)** is a collection of 18 video datasets grouped into 5 categories (anomaly, gesture, daily, sports, and instructional), which covers a diverse set of real-world applications. | Provide a detailed description of the following dataset: BEAR |
VR-Folding | **VR-Folding** contains garment meshes of 4 categories from CLOTH3D dataset, namely Shirt, Pants, Top and Skirt. For flattening task, there are 5871 videos which contain 585K frames in total. For folding task, there are 3896 videos which contain 204K frames in total. The data for each frame include multi-view RGB-D ima... | Provide a detailed description of the following dataset: VR-Folding |
MMHS150k | Existing hate speech datasets contain only textual data. We create a new manually annotated multimodal hate speech dataset formed by 150,000 tweets, each one of them containing text and an image. We call the dataset MMHS150K. | Provide a detailed description of the following dataset: MMHS150k |
MSLS | The largest and most diverse dataset for lifelong place recognition from image sequences in urban and suburban settings. | Provide a detailed description of the following dataset: MSLS |
ARKitTrack | **ARKitTrack** is a new RGB-D tracking dataset for both static and dynamic scenes captured by consumer-grade LiDAR scanners equipped on Apple's iPhone and iPad. ARKitTrack contains 300 RGBD sequences, 455 targets, and 229.7K video frames in total. This dataset has 123.9K pixel-level target masks along with the bounding... | Provide a detailed description of the following dataset: ARKitTrack |
HAMMER | **HAMMER** dataset contains 13 Scenes. Each scene has two setups, with/without objects (with : scene includes several objects with various surface material, without : scene with only backgrounds - naked) and each scene has two camera trajectories. Each trajectories composed with roughly 300 frames, which adds up to 16k... | Provide a detailed description of the following dataset: HAMMER |
CelebV-Text | **CelebV-Text** comprises 70,000 in-the-wild face video clips with diverse visual content, each paired with 20 texts generated using the proposed semi-automatic text generation strategy. The provided texts describes both static and dynamic attributes precisely. | Provide a detailed description of the following dataset: CelebV-Text |
CIRCO | **CIRCO (Composed Image Retrieval on Common Objects in context)** is an open-domain benchmarking dataset for Composed Image Retrieval (CIR) based on real-world images from COCO 2017 unlabeled set. It is the first CIR dataset with multiple ground truths and aims to address the problem of false negatives in existing data... | Provide a detailed description of the following dataset: CIRCO |
IHDP | The Infant Health and Development Program (IHDP) is a randomized controlled study designed to evaluate the effect of home visit from specialist doctors on the cognitive test scores of premature infants. The datasets is first used for benchmarking treatment effect estimation algorithms in Hill [35], where selection bias... | Provide a detailed description of the following dataset: IHDP |
Jobs | The Jobs dataset by LaLonde [36] is a widely used benchmark in the causal inference community, where the treatment is job training and the outcomes are income and employment status after training. The dataset includes 8 covariates such as age, education, and previous earnings. Our goal is to predict unemployment, using... | Provide a detailed description of the following dataset: Jobs |
Hi4D | **Hi4D** contains 4D textured scans of 20 subject pairs, 100 sequences, and a total of more than 11K frames. Hi4D contains rich interaction centric annotations in 2D and 3D alongside accurately registered parametric body models. | Provide a detailed description of the following dataset: Hi4D |
AGIQA-1K | AI Generated Content (AIGC) refers to any form of content, such as text, images, audio, or video, that is created with the help of artificial intelligence technology. With the flourishing development of deep learning, the efficiency of AIGC generation has increased, and AI-Generated Image (AGI) is becoming more prevale... | Provide a detailed description of the following dataset: AGIQA-1K |
OLD French Coronavirus Screening Data | The RT-PCR screening tests used and the results of which are reported in SI-DEP made it possible to suspect the presence of the worrisome variant (VOC) Alpha (20I/501Y.V1) and indistinctly from the VOC Beta (20H/501Y. V2) or Gamma (20J/501Y.V3). This screening strategy targeting Alpha, Beta and Gamma VOCs is no longer ... | Provide a detailed description of the following dataset: OLD French Coronavirus Screening Data |
Fraunhofer Portugal AICOS EDoF Dataset | The Fraunhofer Portugal AICOS EDoF Dataset was produced within the TAMI project and is composed of images of microscopic fields of view (FOV) of Liquid-based Cervical Cytology (LBC) samples. A total of 15 LBC samples were supplied by the Pathology Services from Hospital Fernando Fonseca and the Portuguese Oncology Inst... | Provide a detailed description of the following dataset: Fraunhofer Portugal AICOS EDoF Dataset |
NYCBike1 | Bike flow data of New York City with grid 16x8. | Provide a detailed description of the following dataset: NYCBike1 |
NYCBike2 | Bike flow data of New York City. | Provide a detailed description of the following dataset: NYCBike2 |
NYCTaxi | Taxi flow data of New York City with grid 20x10. | Provide a detailed description of the following dataset: NYCTaxi |
MELON | 1. A unique dataset comprising multimodal creative and designed documents containing images with corresponding captions paired with music based on around 50mood/themes.
2. Motivation: To enhance user experience and to increase accessibility to wider community, motivate research in cross-modal retrieval field.
3.... | Provide a detailed description of the following dataset: MELON |
ARMBench | **ARMBench** is a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. ARMBench contains images, videos, and metadata that corresponds to 235K+ pick-and-place activities on 190K+ unique objects. The data is captured at different stages of manipulation, i.e., pre-pick, du... | Provide a detailed description of the following dataset: ARMBench |
WikiTableSet | WikiTableSet is a large publicly available image-based table recognition dataset in three languages built from Wikipedia.
WikiTableSet contains nearly 4 million English table images, 590K Japanese table images, 640k French table images with corresponding HTML representation, and cell bounding boxes.
We build a Wikipe... | Provide a detailed description of the following dataset: WikiTableSet |
SemanticKITTI-C | #### 🤖 Robo3D - The SemanticKITTI-C Benchmark
SemanticKITTI-C is an evaluation benchmark heading toward robust and reliable 3D semantic segmentation in autonomous driving. With it, we probe the robustness of 3D segmentors under out-of-distribution (OoD) scenarios against corruptions that occur in the real-world env... | Provide a detailed description of the following dataset: SemanticKITTI-C |
KITTI-C | #### 🤖 Robo3D - The KITTI-C Benchmark
KITTI-C is an evaluation benchmark heading toward robust and reliable 3D object detection in autonomous driving. With it, we probe the robustness of 3D detectors under out-of-distribution (OoD) scenarios against corruptions that occur in the real-world environment. Specifically... | Provide a detailed description of the following dataset: KITTI-C |
nuScenes-C | #### 🤖 Robo3D - The nuScenes-C Benchmark
nuScenes-C is an evaluation benchmark heading toward robust and reliable 3D perception in autonomous driving. With it, we probe the robustness of 3D detectors and segmentors under out-of-distribution (OoD) scenarios against corruptions that occur in the real-world environmen... | Provide a detailed description of the following dataset: nuScenes-C |
WOD-C | #### 🤖 Robo3D - The WOD-C Benchmark
WOD-C is an evaluation benchmark heading toward robust and reliable 3D perception in autonomous driving. With it, we probe the robustness of 3D detectors and segmentors under out-of-distribution (OoD) scenarios against corruptions that occur in the real-world environment. Specifi... | Provide a detailed description of the following dataset: WOD-C |
CAIS | We collect utterances from the Chinese Artificial Intelligence Speakers (CAIS), and annotate them with slot tags and intent labels. The training, validation and test sets are split by the distribution of intents, where detailed statistics are provided in the supplementary material. Since the utterances are collected f... | Provide a detailed description of the following dataset: CAIS |
HumanEval-X | HumanEval-X is a benchmark for evaluating the multilingual ability of code generative models. It consists of 820 high-quality human-crafted data samples (each with test cases) in Python, C++, Java, JavaScript, and Go, and can be used for various tasks, such as code generation and translation. | Provide a detailed description of the following dataset: HumanEval-X |
HiREST | **HiREST (HIerarchical REtrieval and STep-captioning)** dataset is a benchmark that covers hierarchical information retrieval and visual/textual stepwise summarization from an instructional video corpus. It consists of 3.4K text-video pairs from a video dataset, where 1.1K videos have annotations of moment spans releva... | Provide a detailed description of the following dataset: HiREST |
OpinionQA | **OpinionQA** is a dataset for evaluating the alignment of LM opinions with those of 60 US demographic groups over topics ranging from abortion to automation. | Provide a detailed description of the following dataset: OpinionQA |
MP-DocVQA | The dataset is aimed to perform Visual Question Answering on multipage industry scanned documents. The questions and answers are reused from Single Page DocVQA (SP-DocVQA) dataset. The images also corresponds to the same in original dataset with previous and posterior pages with a limit of up to 20 pages per document. | Provide a detailed description of the following dataset: MP-DocVQA |
S&P 500 Pair Trading | A pool of real stocks from S&P 500 for recent 21 years from 01/02/2000 to 12/31/2020.
We filter stocks that have missing data throughout the whole period, resulting in 150 stocks with 5,284 trading days. | Provide a detailed description of the following dataset: S&P 500 Pair Trading |
CSI 300 Pair Trading | A daily emerging stock market dataset (Chinese CSI 300 dataset) including 300 stocks and 5,088 time steps from the CSMAR database. We construct our stock dataset using a pool of stocks from the CSI 300 index for the last 21 years, from 01/02/2000 to 12/31/2020. Instead of all stocks in the market, we select the stocks ... | Provide a detailed description of the following dataset: CSI 300 Pair Trading |
NBA player performance prediction dataset | The dataset covers the 2022-23 NBA regular season (2022-10-18 to 2023-01-20) which contains 691 games in 92 game days. There are 582 active players among the 30 teams. Besides 7 basic statistics, we collected 3 tracking statistics, and 3 advanced statistics. We use tracking statistics to more accurately reflect players... | Provide a detailed description of the following dataset: NBA player performance prediction dataset |
pm2.5 dataset | pm2.5 time series data | Provide a detailed description of the following dataset: pm2.5 dataset |
U2OS | The archive contains original images from U2OS cells stained with Hoechst 33342 as PNG files. It also contains images (as Photoshop and GIMP files) showing hand-segmentation of the Hoechst images into regions containing single nuclei. | Provide a detailed description of the following dataset: U2OS |
NIH3T3 | The archive contains original images from NIH3T3 cells stained with Hoechst 33342 as PNG files. It also contains images (as Photoshop and GIMP files) showing hand-segmentation of the Hoechst images into regions containing single nuclei. | Provide a detailed description of the following dataset: NIH3T3 |
PMC-OA | **PMC-OA** is a large-scale dataset that contains 1.65M image-text pairs. The figures and captions from PubMed Central, 2,478,267 available papers are covered and 12,211,907 figure-caption pairs are extracted. | Provide a detailed description of the following dataset: PMC-OA |
EdAcc | **The Edinburgh International Accents of English Corpus (EdAcc)** is a new automatic speech recognition (ASR) dataset composed of 40 hours of English dyadic conversations between speakers with a diverse set of accents. EdAcc includes a wide range of first and second-language varieties of English and a linguistic backgr... | Provide a detailed description of the following dataset: EdAcc |
CIRCLE | **CIRCLE** is a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. | Provide a detailed description of the following dataset: CIRCLE |
ConductorMotion100 | We construct a large-scale conducting motion dataset, named ConductorMotion100, by deploying pose estimation on conductor view videos of concert performance recordings collected from online video platforms. The construction of ConductorMotion100 removes the need for expensive motion-capture equipment and makes full use... | Provide a detailed description of the following dataset: ConductorMotion100 |
UnAV-100 | Existing audio-visual event localization (AVE) handles manually trimmed videos with only a single instance in each of them. However, this setting is unrealistic as natural videos often contain numerous audio-visual events with different categories. To better adapt to real-life applications, we focus on the task of dens... | Provide a detailed description of the following dataset: UnAV-100 |
xCodeEval | xCodeEval is one of the largest **executable** multilingual multitask benchmarks consisting of 17 programming languages with execution-level parallelism. It features a total of seven tasks involving code understanding, generation, translation, and retrieval, and **it employs an execution-based evaluation** instead of t... | Provide a detailed description of the following dataset: xCodeEval |
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