dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
SUDOER | The dataset aims to provide system prompts and user prompts for assistant. You should make random pairs and compute human preference for both system prompt obedience and user prompt relevance through A/B testing. | Provide a detailed description of the following dataset: SUDOER |
neuronIO | ## Single cortical neurons as deep artificial neural networks
This dataset contains training and testing subsets of the input/output relationship of a single cortical layer 5 pyramidal cell (L5PC) neuron at 1ms single spike temporal resolution.
The data is obtained via a simulation that contains all of the curren... | Provide a detailed description of the following dataset: neuronIO |
UruDendro | 64 RGB wood cross-section images with their ring and pith annotations | Provide a detailed description of the following dataset: UruDendro |
100STLYE-Labelled | Over 4 million frames of motion capture data for 100 different styles of locomotion. Can be used for animation, human motion and sequence modelling research.
This version of the dataset includes the features extracted from the raw motion capture data. This includes local phases, foot contacts, joint positions, joint... | Provide a detailed description of the following dataset: 100STLYE-Labelled |
satp-zsm-stage2 | This is the replication data for the paper: "Crossing the Linguistic Causeway: Ethnonational Differences on Soundscape Attributes in Bahasa Melayu". | Provide a detailed description of the following dataset: satp-zsm-stage2 |
Soundscape Attributes Translation Project (SATP) Dataset | The data and audio included here were collected for the Soundscape Attributes Translation Project (SATP). First introduced in Aletta et. al. (2020), the SATP is an attempt to provide validated translations of soundscape attributes in languages other than English. The recordings were used for headphones - based listenin... | Provide a detailed description of the following dataset: Soundscape Attributes Translation Project (SATP) Dataset |
MiniWob++ | MiniWob++ is a suite of web-browser based tasks introduced in Liu et al. (2018) (an extension of the earlier MiniWob task suite (Shi et al., 2017)). Tasks range from simple button clicking to complex form-filling, for example, to book a flight when given particular instructions (Fig. 1a).
Programmatic rewards are avai... | Provide a detailed description of the following dataset: MiniWob++ |
SAGC-A68 | The analysis of building models for usable area, building safety, and energy efficiency requires accurate classification data of spaces and space elements. To reduce input model preparation effort and errors, automated classification of spaces and space elements is desirable. Although existing space function classifier... | Provide a detailed description of the following dataset: SAGC-A68 |
LAGENDA | The LAGENDA dataset is a large-scale dataset with age and gender annotations for face and body bounding boxes. The dataset consists of 67,159 images from the Open Images Dataset and comprises 84,192 pairs (FaceCrop, BodyCrop). This dataset offers a high level of diversity, encompassing various scenes and domains. It co... | Provide a detailed description of the following dataset: LAGENDA |
ConvSumX | **ConvSumX** is a cross-lingual conversation summarization benchmark, through a new annotation schema that explicitly considers source input context. ConvSumX consists of 2 sub-tasks under different real-world scenarios, with each covering 3 language directions. | Provide a detailed description of the following dataset: ConvSumX |
BeaverTails | **BeaverTails** is a dataset aimed at fostering research on safety alignment in large language models (LLMs). This dataset uniquely separates annotations of helpfulness and harmlessness for question-answering pairs, thus offering distinct perspectives on these crucial attributes. In total, the authors have compiled saf... | Provide a detailed description of the following dataset: BeaverTails |
IU X-Ray | IU X-ray (Demner-Fushman et al., 2016) is a set of chest X-ray images paired with their corresponding diagnostic reports. The dataset contains 7,470 pairs of images and reports. | Provide a detailed description of the following dataset: IU X-Ray |
Peir Gross | Peir Gross (Jing et al., 2018) was collected with descriptions in the Gross sub-collection from PEIR digital library, resulting in 7.442 image-caption pairs from 21 different sub-categories. Each caption contains only one sentence. | Provide a detailed description of the following dataset: Peir Gross |
R2C7K | We consider the problem of referring camouflaged object detection (Ref-COD), a new task that aims to segment specified camouflaged objects based on a small set of referring images with salient target objects. | Provide a detailed description of the following dataset: R2C7K |
SemanticSpray Dataset | [Homepage](https://semantic-spray-dataset.github.io/) | [GitHub](https://github.com/aldipiroli/semantic_spray_dataset)
LiDARs are one of the main sensors used for autonomous driving applications, providing accurate depth estimation regardless of lighting conditions. However, they are severely affected by adverse wea... | Provide a detailed description of the following dataset: SemanticSpray Dataset |
10X PBMC (92k) Zheng et. al. 2017 | The data is provided by 10x Genomics under "Single Cell 3' Paper: Zheng et al. 2017 (v1 Chemistry)" and consists of data from the following 9 cell types: CD4+/CD45RA+/CD25- naïve T cells, CD4+ helper T cells, CD4+/CD25+ regulatory T cells, CD4+/CD45RO+ memory T cells, CD8+/CD45RA+ naïve cytotoxic T cells, CD8+ cytotoxi... | Provide a detailed description of the following dataset: 10X PBMC (92k) Zheng et. al. 2017 |
CODE-15% | A dataset of 12-lead ECGs with annotations. The dataset contains 345 779 exams from 233 770 patients. It was obtained through stratified sampling from the CODE dataset ( 15% of the patients). The data was collected by the Telehealth Network of Minas Gerais in the period between 2010 and 2016. | Provide a detailed description of the following dataset: CODE-15% |
PTB-XL | Electrocardiography (ECG) is a key diagnostic tool to assess the cardiac condition of a patient. Automatic ECG interpretation algorithms as diagnosis support systems promise large reliefs for the medical personnel - only on the basis of the number of ECGs that are routinely taken. However, the development of such algor... | Provide a detailed description of the following dataset: PTB-XL |
OCFR-LFW | A occluded version of the LFW dataset for occluded face recognition verification. Uses structured occlusions generated to seem more realistic. | Provide a detailed description of the following dataset: OCFR-LFW |
CCIC | The dataset contains concrete images having cracks. The data is collected from various METU Campus Buildings.
The dataset is divided into two as negative and positive crack images for image classification.
Each class has 20000images with a total of 40000 images with 227 x 227 pixels with RGB channels.
The dataset ... | Provide a detailed description of the following dataset: CCIC |
Multicenter dataset of simulated neuroimaging features - quadratic relationship with age | A detailed description of this dataset can be found in the Zenodo repository: https://zenodo.org/record/8119042#.ZK-jJC9BxhE | Provide a detailed description of the following dataset: Multicenter dataset of simulated neuroimaging features - quadratic relationship with age |
Multicenter dataset of neuroimaging features (part I) | A detailed description of this dataset can be found in the Zenodo repository: https://zenodo.org/record/7845311#.ZK-jty9BxhE | Provide a detailed description of the following dataset: Multicenter dataset of neuroimaging features (part I) |
Multicenter dataset of neuroimaging features (part II) | A detailed description of this dataset can be found in the Zenodo repository: https://zenodo.org/record/7845361#.ZK-k7y9BxhE | Provide a detailed description of the following dataset: Multicenter dataset of neuroimaging features (part II) |
Subjective Perception of Active Noise Reduction (SPANR) | This repository contains replication data to the paper titled: "Anti-noise window: subjective perception of active noise reduction and effect of informational masking" | Provide a detailed description of the following dataset: Subjective Perception of Active Noise Reduction (SPANR) |
TRansPose | **TRansPose** is a large-scale multispectral dataset that combines stereo RGB-D, TIR (TIR) images, and object poses to promote transparent object research. The dataset includes 99 transparent objects, encompassing 43 household items, 27 recyclable trashes, 29 chemical laboratory equivalents, and 12 non-transparent obje... | Provide a detailed description of the following dataset: TRansPose |
MMBench | **MMBench** is a multi-modality benchmark. It methodically develops a comprehensive evaluation pipeline, primarily comprised of two elements. The first element is a meticulously curated dataset that surpasses existing similar benchmarks in terms of the number and variety of evaluation questions and abilities. The secon... | Provide a detailed description of the following dataset: MMBench |
RAISE-LPBF | Laser powder bed fusion (LBPF) is the additive manufacturing (3D printing) process for metals. RAISE-LPBF is a large dataset on the effect of laser power and laser dot speed in 316L stainless steel bulk material. Both process parameters are independently sampled for each scan line from a continuous distribution, so in... | Provide a detailed description of the following dataset: RAISE-LPBF |
HLW | We introduce Horizon Lines in the Wild (HLW), a large dataset of real-world images with
labeled horizon lines, captured in a diverse set of environments. The dataset is available
for download at our project website [1]. We begin by characterizing limitations in existing
datasets for evaluating horizon line detection... | Provide a detailed description of the following dataset: HLW |
Parcel3D | Synthetic dataset of over 13,000 images of damaged and intact parcels with full 2D and 3D annotations in the COCO format. For details see our [paper](https://openaccess.thecvf.com/content/CVPR2023W/VISION/html/Naumann_Parcel3D_Shape_Reconstruction_From_Single_RGB_Images_for_Applications_in_CVPRW_2023_paper.html) and fo... | Provide a detailed description of the following dataset: Parcel3D |
CBTex | Dataset of >200 synthetic cardboard texture images that were rendered with DoubeGum's cardboard shader in Blender. Used to generate [Parcel3D](https://a-nau.github.io/parcel3d/), the dataset for our [paper](https://openaccess.thecvf.com/content/CVPR2023W/VISION/html/Naumann_Parcel3D_Shape_Reconstruction_From_Single_RGB... | Provide a detailed description of the following dataset: CBTex |
Parcel2D Real | Real-world dataset of ~400 images of cuboid-shaped parcels with full 2D and 3D annotations in the COCO format. | Provide a detailed description of the following dataset: Parcel2D Real |
HabiCrowd | HabiCrowd, a new dataset and benchmark for crowd-aware visual navigation that surpasses other benchmarks in terms of human diversity and computational utilization. HabiCrowd can be utilized to study crowd-aware visual navigation tasks. A notable feature of HabiCrowd is that our crowd-aware settings is 3D, which is scar... | Provide a detailed description of the following dataset: HabiCrowd |
Segmentation in the Wild | Recent advances in language-image pre-training has witnessed the emerging field of building transferable systems that can effortlessly adapt to a wide range of computer vision & multimodal tasks in the wild. This also poses a challenge to evaluate the transferability of these models due to the lack of easy-to-use evalu... | Provide a detailed description of the following dataset: Segmentation in the Wild |
WaterScenes | A Multi-Task 4D Radar-Camera Fusion Dataset for Autonomous Driving on Water Surfaces description of the dataset
* WaterScenes, the first multi-task 4D radar-camera fusion dataset on water surfaces, which offers data from multiple sensors, including a 4D radar, monocular camera, GPS, and IMU. It can be applied in mu... | Provide a detailed description of the following dataset: WaterScenes |
BDD-QA | **BDD-QA** is distinguished by its encompassing range of traffic actions, crafted to rigorously evaluate a model's decision-making abilities in traffic scenario. This makes it a potent tool for high-level decision-making research within traffic contexts, including autonomous driving developments. | Provide a detailed description of the following dataset: BDD-QA |
HDT-QA | HDT-QA, coupled with driving manuals, offers an extensive compendium of driving instructions and driving knowledge tests across all 51 states of the US. This resource is beneficial for assessing the incorporation and impact of traffic knowledge within intelligent driving systems, marking a crucial stride towards more a... | Provide a detailed description of the following dataset: HDT-QA |
Complex-TV-QA | The Complex-TV-QA dataset, to our knowledge, is the inaugural resource that provides human-annotated, detailed video captions within traffic scenarios, alongside complex reasoning questions. This novel dataset not only stands as a vital tool for evaluating language models in real-world video-QA and video-reasoning rese... | Provide a detailed description of the following dataset: Complex-TV-QA |
NEU dataset | Data set used in the work One-Shot Recognition of Manufacturing Defects in Steel Surfaces | Provide a detailed description of the following dataset: NEU dataset |
NILUT | Read all the details about the dataset in our paper "NILUT: Conditional Neural Implicit 3D Lookup Tables for Image Enhancement"
* We host the dataset in Kaggle: https://www.kaggle.com/datasets/photolab/nilut-3d-lut-dataset
* More information in our repo: https://github.com/mv-lab/nilut | Provide a detailed description of the following dataset: NILUT |
RidgeBase | Contactless fingerprint matching using smartphone cameras can alleviate major challenges of traditional fingerprint systems including hygienic acquisition, portability and presentation attacks. However, development of practical and robust contactless fingerprint matching techniques is constrained by the limited availab... | Provide a detailed description of the following dataset: RidgeBase |
SHD - Adding | This dataset is based on the Spiking Heidelberg Digits (SHD) dataset. Sample inputs consist of two spike encoded digits sampled uniformly at random from the SHD dataset and concatenated, with the target being the sum of the digits (irrespective of language). The train and test split remain the same, with the test set c... | Provide a detailed description of the following dataset: SHD - Adding |
WYWEB | An evaluation bentchmark for classical Chinese. | Provide a detailed description of the following dataset: WYWEB |
RePoGen | Synthetic humans generated by the RePoGen method. | Provide a detailed description of the following dataset: RePoGen |
CPAP | Kang et al.'s Markovian model for treatment adherence in obstructive sleep apnea.
Kang, Yuncheol, et al. "Markov models for treatment adherence in obstructive sleep apnea." IIE Annual Conference. Proceedings. Institute of Industrial and Systems Engineers (IISE), 2013.
Kang, Yuncheol, et al. "Modelling adherence b... | Provide a detailed description of the following dataset: CPAP |
PatchDB | PatchDB is a large-scale security patch dataset that contains around 12K security patches and 24K non-security patches from the real world. | Provide a detailed description of the following dataset: PatchDB |
PolypGen | Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp’s number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they a... | Provide a detailed description of the following dataset: PolypGen |
DiPCo | We present a speech data corpus that simulates a "dinner party" scenario taking place in an everyday home environment. The corpus was created by recording multiple groups of four Amazon employee volunteers having a natural conversation in English around a dining table. The participants were recorded by a single-channel... | Provide a detailed description of the following dataset: DiPCo |
Zucker HRI Dataset | **Zucker HRI Dataset** contains two different agent types (robot and human) in several scenarios. The robot switched between 3 different motion controllers (Linear, NHTTC, and CADRL) over multiple different scenarios with different permutations of human agents. There are also scenes without the robot for a baseline. | Provide a detailed description of the following dataset: Zucker HRI Dataset |
Rad-ReStruct | Rad-ReStruct is a fine-grained structured reporting dataset for Chest X-Ray images. The structured reporting process is modeled as a hierarchical VQA task and the task is recognizing different findings in different body regions and predicting their attributes. | Provide a detailed description of the following dataset: Rad-ReStruct |
satnet-sudoku | A set of easy Sudoku instances used in the SATNet paper for training SatNet on how to learn to play Sudoku.
The instances are easy (plenty of hints) and it is therefore rather easy to get high accuracy on these. More challenging instances are available in the rrn-sudoku dataset. | Provide a detailed description of the following dataset: satnet-sudoku |
rrn-sudoku | A set of 180,000 Sudoku grids with a variable number of hints from the minimal number of 17 (extremely hard instances) to 34 (easy instances), with 10,000 instances per level of hardness.
Training how to play the hardest Sudoku instances is a bit of a challenge. | Provide a detailed description of the following dataset: rrn-sudoku |
many-solutions-sudoku | A data set of Sudoku grids with more than one solution.
This was introduced to train on logical reasoning problems with non-unique solutions. | Provide a detailed description of the following dataset: many-solutions-sudoku |
Protein structures Ingraham | A data set introduced for training on the protein design task. | Provide a detailed description of the following dataset: Protein structures Ingraham |
T2I-CompBench | T2I-CompBench is a comprehensive benchmark for open-world compositional text-to-image generation, consisting of 6,000 compositional textual prompts from 3 categories (attribute binding, object relationships, and complex compositions) and 6 sub-categories (color binding, shape binding, texture binding, spatial relations... | Provide a detailed description of the following dataset: T2I-CompBench |
InternVid | **InternVid** is a large-scale video-centric multimodal dataset that enables learning powerful and transferable video-text representations for multimodAL understanding and generation. The InternVid dataset contains over 7 million videos lasting nearly 760K hours, yielding 234M video clips accompanied by detailed descri... | Provide a detailed description of the following dataset: InternVid |
COLLIE-v1 | **COLLIE-v1** is a dataset with 2080 instances comprising 13 constraint structures designed for text generation under constraints. It is a grammar-based framework that allows the specification of rich, compositional constraints with diverse generation levels (word, sentence, paragraph, passage). | Provide a detailed description of the following dataset: COLLIE-v1 |
Experimental Results for "A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models" | This package contains the raw data / logs (fetched from WandB) for the experiments of the following publication:
O. Arenz, P. Dahlinger, Z. Ye, M. Volpp, and G. Neumann. A unified perspective on natural gradient variational inference with gaussian mixture models. Transactions on Machine Learning Research, 2023. URL:... | Provide a detailed description of the following dataset: Experimental Results for "A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models" |
OCTID | An open-source Optical Coherence Tomography Image Database containing different retinal OCT images with various pathological conditions. This comprehensive open-access database contains over 500 high-resolution images categorized into different pathological conditions. The image classes include Normal (NO), Macular Hol... | Provide a detailed description of the following dataset: OCTID |
VideoInstruct | Video Instruction Dataset is used to train Video-ChatGPT. It consists of 100,000 high-quality video instruction pairs. employs a combination of human-assisted and semi-automatic annotation techniques, aiming to produce high-quality video instruction data. These methods create question-answer pairs related to
1. Vide... | Provide a detailed description of the following dataset: VideoInstruct |
TSN-FlexTest Traffic Streams for Spot Robot, Tactile Internet, and Generic Data | In this dataset, we provide detailed traffic stream data for the Spot robot, including both the Spot robot control traffic stream and the Spot video stream. The Spot robot traffic streams provide realistic traffic data for communication network evaluations, e.g., for measurements with the TSN FlexText testbed. Furtherm... | Provide a detailed description of the following dataset: TSN-FlexTest Traffic Streams for Spot Robot, Tactile Internet, and Generic Data |
SOD4SB | The **Small Object Detection for Spotting Birds (SOD4SB)** dataset is a dataset consisting of 39,070 images including 137,121 bird instances. The SOD4SD dataset contains a wide variety of small bird types and a variety of scenes. | Provide a detailed description of the following dataset: SOD4SB |
FathomNet2023 | The FathomNet2023 competition dataset is a subset of the [broader FathomNet marine image repository](https://fathomnet.org/). The training and test images for the competition were all collected in the Monterey Bay Area between the surface and 1300 meters depth by the Monterey Bay Aquarium Research Institute. The images... | Provide a detailed description of the following dataset: FathomNet2023 |
OpenLane-V2 test | **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 test |
DialogStudio | DialogStudio, a meticulously curated collection of dialogue datasets. These datasets are unified under a consistent format while retaining their original information. We incorporate domain-aware prompts and identify dataset licenses, making DialogStudio an exceptionally rich and diverse resource for dialogue research a... | Provide a detailed description of the following dataset: DialogStudio |
DNA-Rendering | **DNA-Rendering** is a large-scale, high-fidelity repository of human performance data for neural actor rendering. It contains over 1500 human subjects, 5000 motion sequences, and 67.5M frames' data volume. Upon the massive collections, the authors provide human subjects with grand categories of pose actions, body shap... | Provide a detailed description of the following dataset: DNA-Rendering |
AitW | **Android in the Wild (AitW)** is a dataset for device-control research which is orders of magnitude larger than current datasets. The dataset contains human demonstrations of device interactions, including the screens and actions, and corresponding natural language instructions. It consists of 715k episodes spanning 3... | Provide a detailed description of the following dataset: AitW |
BIOSCAN_1M_Insect Dataset | In an effort to catalog insect biodiversity, we propose a new large dataset of hand-labelled insect images, the BIOSCAN-1M Insect Dataset. Each record is taxonomically classified by an expert, and also has associated genetic information including raw nucleotide barcode sequences and assigned barcode index numbers, whic... | Provide a detailed description of the following dataset: BIOSCAN_1M_Insect Dataset |
LLNeRF Dataset | **LLNeRF Dataset** is a real-world dataset as a benchmark for model learning and evaluation. To obtain real low-illumination images with real noise distributions, photos are taken at nighttime outdoor scenes or low-light indoor scenes containing diverse objects. Since the ISP operations are device dependent and the noi... | Provide a detailed description of the following dataset: LLNeRF Dataset |
MeDAL Retina Dataset | Our primary objective in creating this dataset is to support researchers in the advancement of algorithms for keypoints detection and the pretraining of large models on retinal images using a self-supervised approach. The keypoints in the dataset have been carefully annotated by students from our lab, ensuring meticulo... | Provide a detailed description of the following dataset: MeDAL Retina Dataset |
AudioSet CC | The subset of audio samples from the AudioSet ontology which are licensed with Creative Commons. This set contains approximately 10,000 samples of 10s long clips, and is freely modifiable and distributable. Each clip has with it, its full label set and unique ID. | Provide a detailed description of the following dataset: AudioSet CC |
Replication Data for: AI Ethics on Blockchain: Topic Analysis on Twitter Data for Blockchain Security | Blockchain has empowered computer systems to be more secure using a distributed network. However, the current blockchain design suffers from fairness issues in transaction ordering. Miners are able to reorder transactions to generate profits, the so-called miner extractable value (MEV). Existing research recognizes MEV... | Provide a detailed description of the following dataset: Replication Data for: AI Ethics on Blockchain: Topic Analysis on Twitter Data for Blockchain Security |
Replication Data for: On the Mechanics of NFT Valuation: AI Ethics and Social Media | As CryptoPunks pioneers the innovation of non-fungible tokens (NFTs) in AI and art, the valuation mechanics of NFTs has become a trending topic. Earlier research identifies the impact of ethics and society on the price prediction of CryptoPunks. Since the booming year of the NFT market in 2021, the discussion of Crypto... | Provide a detailed description of the following dataset: Replication Data for: On the Mechanics of NFT Valuation: AI Ethics and Social Media |
Replication Data for: AI Ethics on Blockchain | Blockchain has empowered computer systems to be more secure using a distributed network. However, the current blockchain design suffers from fairness issues in transaction ordering. Miners are able to reorder transactions to generate profits, the so-called miner extractable value (MEV). Existing research recognizes MEV... | Provide a detailed description of the following dataset: Replication Data for: AI Ethics on Blockchain |
Replication Data for: On the Mechanics of NFT Valuation | As CryptoPunks pioneers the innovation of non-fungible tokens (NFTs) in AI and art, the valuation mechanics of NFTs has become a trending topic. Earlier research identifies the impact of ethics and society on the price prediction of CryptoPunks. Since the booming year of the NFT market in 2021, the discussion of Crypto... | Provide a detailed description of the following dataset: Replication Data for: On the Mechanics of NFT Valuation |
Replication Data for: Blockchain Network Analysis | Decentralized finance (DeFi) is known for its unique mechanism design, which applies smart contracts to facilitate peer-to-peer transactions. The decentralized bank is a typical DeFi application. Ideally, a decentralized bank should be decentralized in the transaction. However, many recent studies have found that decen... | Provide a detailed description of the following dataset: Replication Data for: Blockchain Network Analysis |
SciBench | **SciBench** is a large-scale scientific problem-solving benchmark suite that aims to systematically examine the reasoning capabilities required for complex scientific problem solving. SciBench contains two carefully curated datasets: an open set featuring a range of collegiate-level scientific problems drawn from math... | Provide a detailed description of the following dataset: SciBench |
The Rambles | Collection of stream of consciousness.
Natural language processing dataset.
Individual thoughts are separated by a double new line. | Provide a detailed description of the following dataset: The Rambles |
DDXPlus | There has been a rapidly growing interest in Automatic Symptom Detection (ASD) and Automatic Diagnosis (AD) systems in the machine learning research literature, aiming to assist doctors in telemedicine services. These systems are designed to interact with patients, collect evidence about their symptoms and relevant ant... | Provide a detailed description of the following dataset: DDXPlus |
Smarty4covid | Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset
and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during
COVID-19 pandemic. The smarty4covid dataset contains audio signa... | Provide a detailed description of the following dataset: Smarty4covid |
CAD | Dataset of primarily English Reddit entries which addresses several limitations of prior work. It (1) contains six conceptually distinct primary categories as well as secondary categories, (2) has labels annotated in the context of the conversation thread, (3) contains rationales and (4) uses an expert-driven group-adj... | Provide a detailed description of the following dataset: CAD |
Rosario Dataset | Agricultural dataset collected on-board out weed removing robot. The dataset is composed by six different sequences in a soybean field and it contains stereo images, IMU measurements, wheel odometry and GPS-RTK (positional ground-truth) | Provide a detailed description of the following dataset: Rosario Dataset |
DPR-ANN | We provide the [code](https://github.com/IntelLabs/DPR-dataset-generator/tree/main) to generate base and query vector datasets for similarity search benchmarking and evaluation on high-dimensional vectors stemming from large language models. With the dense passage retriever (DPR) [[1]](#1), we encode text snippets from... | Provide a detailed description of the following dataset: DPR-ANN |
COCO-O | COCO-O(ut-of-distribution) contains 6 domains (sketch, cartoon, painting, weather, handmake, tattoo) of COCO objects which are hard to be detected by most existing detectors. The dataset has a total of 6,782 images and 26,624 labelled bounding boxes. | Provide a detailed description of the following dataset: COCO-O |
grobid-quantities-holdout | The dataset is described here:
https://grobid-quantities.readthedocs.io/en/latest/guidelines.html | Provide a detailed description of the following dataset: grobid-quantities-holdout |
SOEval | SOEVAL is created by us by mining questions from StackOverflow. Our goal was to create a prompt dataset that reflects the real-life needs of software developers. To build this dataset, we first collected 500 popular and recent questions with Python and Java tags for each. From these 1,000 questions, we applied a set of... | Provide a detailed description of the following dataset: SOEval |
Inria building dataset | **Inria building dataset** contains 360 images (5120×5120) collected from 5 cities (Austin, Chicago, Kitsap, Tyrol, and Vienna) | Provide a detailed description of the following dataset: Inria building dataset |
SK-VG | **SK-VG** is a dataset for Scene Knowledge-guided Visual Grounding, where the image content and referring expressions are not sufficient to ground the target objects, forcing the models to have a reasoning ability on the long-form scene knowledge. To perform this task, SK-VG is the first dataset of the fourth type, whe... | Provide a detailed description of the following dataset: SK-VG |
OpenGDA | **OpenGDA** is a benchmark for evaluating graph domain adaptation models. It provides abundant pre-processed and unified datasets for different types of tasks (node, edge, graph). They originate from diverse scenarios, covering web information systems, urban systems and natural systems. Furthermore, it integrates state... | Provide a detailed description of the following dataset: OpenGDA |
Building3D | **Building3D** is an urban-scale dataset consisting of more than 160 thousands buildings along with corresponding point clouds, mesh and wireframe models, covering 16 cities in Estonia about 998 Km2. Besides mesh models and real-world LiDAR point clouds, it also includes wireframe models. | Provide a detailed description of the following dataset: Building3D |
Massachusetts building dataset | The official dataset contains a training set (137 images), a validation set (4 images), and a testing set (10 images) | Provide a detailed description of the following dataset: Massachusetts building dataset |
Replay | **Replay** is a collection of multi-view, multi-modal videos of humans interacting socially. Each scene is filmed in high production quality, from different viewpoints with several static cameras, as well as wearable action cameras, and recorded with a large array of microphones at different positions in the room. The ... | Provide a detailed description of the following dataset: Replay |
Description Detection Dataset | **Description Detection Dataset** ($D^3$, /dikju:b/) is an attempt at creating a next-generation object detection dataset. Unlike traditional detection datasets, the class names of the objects are no longer simple nouns or noun phrases, but rather complex and descriptive, such as `a dog not being held by a leash`. For ... | Provide a detailed description of the following dataset: Description Detection Dataset |
ARTE | The ARTE database, so far, contains 13 acoustic environments that were recorded with a purpose-built 62-channel microphone array in various locations around Sydney (Australia), and was decoded into the higher-order Ambisonics (HOA) format.
For each acoustic environment the following files are provided:
HOA enviro... | Provide a detailed description of the following dataset: ARTE |
REFCAT | Internet Archive Scholar Reference Dataset. | Provide a detailed description of the following dataset: REFCAT |
Can you predict product backorder? | **Problem Statement**
Material backorder is a common problem in a supply chain system, impacting an inventory system's service level and effectiveness. Identifying parts with the highest chances of shortage prior to their occurrence can present a high opportunity to improve an overall company’s performance. In this ... | Provide a detailed description of the following dataset: Can you predict product backorder? |
LAION-Aesthetics V2 6.5+ | * A subset of the LAION 5B samples with English captions, obtained using LAION-Aesthetics_Predictor V2
* 625K image-text pairs with predicted aesthetics scores of 6.5 or higher
* available at https://huggingface.co/datasets/ChristophSchuhmann/improved_aesthetics_6.5plus | Provide a detailed description of the following dataset: LAION-Aesthetics V2 6.5+ |
DFEW | Recently, facial expression recognition (FER) in the wild has gained
a lot of researchers’ attention because it is a valuable topic to enable the FER techniques to move from the laboratory to the real
applications. In this paper, we focus on this challenging but interesting topic and make contributions from three asp... | Provide a detailed description of the following dataset: DFEW |
FERV39k | Current benchmarks for facial expression recognition (FER) mainly focus on static images, while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether performances of existing methods remain satisfactory in real-world application-oriented scenes. For example, the “Happy” expression with... | Provide a detailed description of the following dataset: FERV39k |
Data and Code from: Naïve Individuals Promote Collective Exploration in Homing Pigeons. | This archive contains raw data, intermediate results, statistics, and figures for the manuscript "Naïve individuals promote collective exploration in homing pigeons"
Once unzipped, the folder structure will look as follow:
- data/ [raw data and intermediate results]
- img/ [all plots in the manuscript]
- scripts/... | Provide a detailed description of the following dataset: Data and Code from: Naïve Individuals Promote Collective Exploration in Homing Pigeons. |
GoodsAD | The GoodsAD dataset contains 6124 images with 6 categories of common supermarket goods. Each category contains multiple goods. All images are acquired with 3000 × 3000 high-resolution. The object locations in the images are not aligned. Most objects are in the center of the images and one image only contains a single o... | Provide a detailed description of the following dataset: GoodsAD |
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