19,997 machine learning datasets
19,997 dataset results
This eye tracking video database can be used to validate visual attention models. This dataset includes 72 videos downloaded from Internet and some synthetic videos generated in the lab. The videos can be classified in four categories, natural and synthetic, with fixed or movement camera. It includes 27 synthetic videos with dynamic pop-out effects. The videos have been selected in order to minimize the influence of the top-down effects.
A large corpus of discourse annotations and relations on ~10K forum threads.
This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:
A corpus of movie quotes, annotated with memorability information, in which one is able to control for both the speaker and the setting of the quotes.
Corpus of domain names scraped from Common Crawl and manually annotated to add word boundaries (e.g. "commoncrawl" to "common crawl").
Benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets and originally used in Livelo & Cheng (2018).
RGB-D images of 60 western dishes, home made. Data was recorded using a Microsoft Kinect V2.
This dataset is being constructed specifically to support research on techniques that bridge the gap between 2D, appearance-based recognition techniques, and fully 3D approaches. It is designed to simulate, in a controlled fashion, realistic surveillance conditions and to probe the efficacy of exploiting 3D models in real scenarios.
GDXray+ is a collection of more than 21.100 X-ray images for the development, testing, and evaluation of image analysis and computer vision algorithms.
A large database of geotagged face images.
Corpus and annotations for the CL-Aff Shared Task - Get it #OffMyChest - from Nanyang Technological University Singapore.
The Hong Kong Cantonese Corpus was collected from transcribed conversations that were recorded between March 1997 and August 1998. About 230,000 Chinese words were collected in the annotated corpus. It contains recordings of spontaneous speech (51 texts) and radio programmes (42 texts), which involve 2 to 4 speakers, with 1 text of monologue. The text were word-segmented, annotated with part-of-speech tagging and Cantonese pronunciation using the romanisation scheme of Linguistic Society of Hong Kong (LSHK).
A database of images with measured probabilities that each picture will be remembered after a single view.
This is a social interaction dataset between two subjects. This dataset consists of RGB and depth images, and tracked skeleton data (i.e. joints 3D coordinates and rotations) acquired by an RGB-D sensor. It includes 8 social activities: {handshake, greeting hug, help walk, help stand-up, fight, push, conversation, call attention}. Each activity was recorded in a period around 40 to 60 seconds of repetitions within the same session at a frame rate of 30 frames per second. The only exceptions are help walking (at a short distance) and help stand-up, which were recorded 4 times to the same session, regardless of the time spent on it.
The Dataset consists of the multimodal facial images of 52 people (14 females, 38 males) obtained by Kinect. The data is captured in two sessions happened at different time period (about half month). In each session, the dataset provides the facial images of each person in 9 states of different facial expressions, different lighting and occlusion conditions: neutral, smile, open mouth, left profile, right profile, occlusion eyes, occlusion mouth, occlusion paper and light on [Figure 1]. All the images are provided in three sources of information: the RGB color image, the depth map (provided in two forms of the bitmap depth image and the text file containing the original depth levels sensed by Kinect) as well as 3D. In addition, the dataset comes with the manual landmarks of 6 positions in the face: left eye, right eye, the tip of nose, left side of mouth, right side of mouth and the chin [Figure 2]. Other information of the person such as gender, year of birth, glasses (this person wea
Court decisions from 2017 and 2018 were selected for the dataset, published online by the Federal Ministry of Justice and Consumer Protection. The documents originate from seven federal courts: Federal Labour Court (BAG), Federal Fiscal Court (BFH), Federal Court of Justice (BGH), Federal Patent Court (BPatG), Federal Social Court (BSG), Federal Constitutional Court (BVerfG) and Federal Administrative Court (BVerwG).
The limit dataset of ~24K sentences that describe literal motion (~14K sentences), and sentences not describing motion or other type of motion (e.g. fictive motion). Senteces were extracted from electronic books categorized as fiction or novels, and a portion from the NetActivity Captions Dataset.
A dataset of female face images assembled for studying the impact of makeup on face recognition.
The MASATI dataset contains color images in dynamic marine environments, and it can be used to evaluate ship detection methods. Each image may contain one or multiple targets in different weather and illumination conditions. The datasets is composed of 7,389 satellite images labeled according to the following seven classes: land, coast, sea, ship, multi, coast-ship, and detail. In addition, labeling with the bounding box for the location of the vessels is also included.
The dataset consists of tweets belonging to #MeToo movement on Twitter, labelled into different categories.