19,997 machine learning datasets
19,997 dataset results
The social vision and language dataset is a large-scale multimodal dataset designed for research into social contextual learning.
BigBIRD is a 3D dataset of 125 objects, with the following data for each object:
The CUHK Face Alignment Database is dataset with 13,466 face images, among which 5, 590 images are from LFW and the remaining 7, 876 images are downloaded from the web. Each face is labeled with the positions of five facial keypoints. 10,000 images are used for training and the remaining 3,466 images for validation.
BelgaLogos is a dataset for logo detection and recognition. The images of BelgaLogos dataset have been provided and are copyrighted by BELGA press agency. They are freely available for research purpose only. The dataset is composed of 10,000 images covering all aspects of life and current affairs: politics and economics, finance and social affairs, sports, culture and personalities. All images are in JPEG format and have been re-sized with a maximum value of height and width equal to 800 pixels, preserving aspect ratio.
CASR is a dataset for cyclist arm signal recognition in videos. It contains 219 annotated arm signal actions on videos of approximately 10 seconds each, containing one or two actions per video.
This dataset consists of a number of sequences that were recorded with a VGA (640x480) event camera (Samsung DVS Gen3) and a conventional RGB camera (Huawei P20 Pro) placed on the windshield of a car driving through Zurich.
Relations in Captions (REC-COCO) is a new dataset that contains associations between caption tokens and bounding boxes in images. REC-COCO is based on the MS-COCO and V-COCO datasets. For each image in V-COCO, we collect their corresponding captions from MS-COCO and automatically align the concept triplet in V-COCO to the tokens in the caption. This requires finding the token for concepts such as PERSON. As a result, REC-COCO contains the captions and the tokens which correspond to each subject and object, as well as the bounding boxes for the subject and object.
The dataset contains gold-standard summary labels for 39 "CSI: Crime Scene Investigation" episodes from seasons 1-5. Each episode contains the full-length screenplay and human annotations for its summary. The annotations include:
This dataset is composed of paired videos of people dancing 3 different music styles: Ballet, Michael Jackson and Salsa. It contains multimodal data (visual data, temporal-graphs and audio) careful-selected from publicly available videos of dancers performing representative movements of the music style and audio data from the respective styles.
Given the difficulty to handle planetary data we provide downloadable files in PNG format from the missions Chang'E-3 and Chang'E-4. In addition to a set of scripts to do the conversion given a different PDS4 Dataset.
The dataset contains 11,913 frame pairs of urban driving footage with and without moving objects, synthetically generated with the CARLA simulator. All frames are available both as RGB images and semantic segmentations. RGB images are non-photorealistic being rendered by a game engine, while semantic segmentations are similar to a real-world segmentations. The dataset is designed to provide a supervision for semantic road inpainting tasks.
Content This dataset contains all utterances of two episodes of South Park (Latin American voices) and two episodes of Archer (Spanish voices). The order of the utterances is shuffled. Each utterance has been annotated based on whether it is sarcastic or not. Sarcastic expressions also contain further annotation based on different theories on sarcasm.
MIRACL-VC1 is a lip-reading dataset including both depth and color images. It can be used for diverse research fields like visual speech recognition, face detection, and biometrics. Fifteen speakers (five men and ten women) positioned in the frustum of an MS Kinect sensor and utter ten times a set of ten words and ten phrases (see the table below). Each instance of the dataset consists of a synchronized sequence of color and depth images (both of 640x480 pixels). The MIRACL-VC1 dataset contains a total number of 3000 instances.
We address the computer-assisted search for prior art by creating a training dataset for supervised machine learning called PatentMatch. It contains pairs of claims from patent applications and semantically corresponding text passages of different degrees from cited patent documents. Each pair has been labeled by technically-skilled patent examiners from the European Patent Office. Accordingly, the label indicates the degree of semantic correspondence (matching), i.e., whether the text passage is prejudicial to the novelty of the claimed invention or not.
We present a dataset of dialogs in which journalists of The Guardian replied to reader comments and identify the reasons why. Based on this data, we formulate the novel task of recommending reader comments to journalists that are worth reading or replying to, i.e., ranking comments in such a way that the top comments are most likely to require the journalists' reaction.
This dataset comprises four files of IDs of either strongly or weakly engaging online news comments (please see the paper for details): "Top comments" are 1) the top 10% comments in the politics section of The Guardian with the largest relative number of replies received (3111 samples) and 2) the top 10% comments in the politics section with the largest relative number of upvotes received (11081 samples)
The WEB-FORUM-52 gold standard comprises (i) 13 web forums from the health domain, (ii) 15 forums obtained from a Wikipedia list of popular forums (https://en.wikipedia.org/wiki/List_of_Internet_forums), (iii) 13 forums mentioned on a list of popular German Web forums (https://www.beliebte-foren.de), (iv) nine forums obtained from WPressBlog (https://www.wpressblog.com/free-forum-posting-sites-list/) and (v) two additional forums. For most forums two web pages (from different threads) were used and stored together with gold standard annotations that have been manually created by domain experts and describe the post text, post date, post user and direct URL to the post.
We announce the release of a new multilingual speaker dataset called NITK-IISc Multilingual Multi-accent Speaker Profiling(NISP) dataset. The dataset contains speech in six different languages -- five Indian languages along with Indian English. The dataset contains speech data from 345 bilingual speakers in India. Each speaker has contributed about 4-5 minutes of data that includes recordings in both English and their mother tongue. The transcript for the text is provided in UTF-8 format. For every speaker, the dataset contains speaker meta-data such as L1, native place, medium of instruction, current residing place etc. In addition the dataset also contains physical parameter information of the speakers such as age, height, shoulder size and weight. We hope that the dataset is useful for a diverse set of research activities including multilingual speaker recognition, language and accent recognition, automatic speech recognition etc.
The LiT.RL POLIT-FALSE-n-LEGIT NEWS DB 2016-2017 contains a total of 274 news articles about U.S. Politics, content-matched in pairs of legitimate and falsified news. The database is free and released under an open license for educational and research purposes.
GQN rooms-ring-camera consist of scenes of a variable number of random objects captured in a square room of size 7x7 units. Wall textures, floor textures as well as the shapes of the objects are randomly chosen within a fixed pool of discrete options. There are 5 possible wall textures (red, green, cerise, orange, yellow), 3 possible floor textures (yellow, white, blue) and 7 possible object shapes (box, sphere, cylinder, capsule, cone, icosahedron and triangle). Each scene contains 1, 2 or 3 objects. In this simplified version of the dataset, the camera only moves on a fixed ring and always faces the center of the room.