19,997 machine learning datasets
19,997 dataset results
Provides 450, 000 relevance annotations and 53 structured queries.
The Omni-MOT is realistic CARLA based large-scale dataset with over 14M frames for multiple vehicle tracking . The dataset comprises 14M+ frames, 250K tracks, 110 million bounding boxes, three weather conditions, three crowd levels and three camera views in five simulated towns.
This data set was created to understand the potential for machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control. These cameras, which have horizon-to-horizon view, offer the potential for an improved view of the traffic environment which can be used to generate better control algorithms.
Open MIC (Open Museum Identification Challenge) contains photos of exhibits captured in 10 distinct exhibition spaces of several museums which showcase paintings, timepieces, sculptures, glassware, relics, science exhibits, natural history pieces, ceramics, pottery, tools and indigenous crafts. The goal of Open MIC is to stimulate research in domain adaptation, egocentric recognition and few-shot learning by providing a testbed complementary to the famous Office 31.
A preliminary dataset of related tables and a corresponding set of natural language questions.
The Out the Window (OTW) dataset is a crowdsourced activity dataset containing 5,668 instances of 17 activities from the NIST Activities in Extended Video (ActEV) challenge. These videos are crowdsourced from workers on the Amazon Mechanical Turk using a novel scenario acting strategy, which collects multiple instances of natural activities per scenario.
A bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts who post English-Arabic tweets regularly.
Anew dataset of facade images from Paris following the Art-deco style.
Contains over 4,500 videos recorded at the entrance doors of buses in normal and cluttered conditions. It also proposes an efficient method for counting people in real-world cluttered scenes related to public transportations using depth videos.
The Permuted bAbi dialog task is an adaptation of the "Dialog bAbI tasks data" dataset released by Facebook. It is used for evaluating end-to-end dialog systems in the restaurant domain. This dataset introduces multiple valid next utterances to the original-bAbI dialog tasks, which allows evaluation of end-to-end goal-oriented dialog systems in a more realistic setting.
PheMT is a phenomenon-wise dataset designed for evaluating the robustness of Japanese-English machine translation systems. The dataset is based on the MTNT dataset, with additional annotations of four linguistic phenomena common in UGC; Proper Noun, Abbreviated Noun, Colloquial Expression, and Variant
A large-scale dataset of user annotations on seven common photographic defects.
The pic2kal benchmark for calorie prediction contains 308,000 images from over 70,000 recipes including photographs, ingredients and instructions, matched with nutritional information.
PicTropes is a dataset of films and the tropes that they use created from the database DBTropes.org.
The Pinterest Complete the Look dataset consists of over 1 million outfits and 4 million objects. It can be used to predict style compatibility between fashion items in order to recommend complementary items that complete an outfit.
The dataset consists of 90 000 color videos that show a planar robot manipulator executing articulated manipulation tasks. More precisely, the manipulator grasps a circular object of random color and size and places it on top of a square object/platform of again random color and size. The initial configurations (location, size and color) of the objects were randomly sampled during generation. Different from other datasets such as the moving MNIST dataset, the samples comprise a goal-oriented task as described, making it more suitable for testing prediction capabilities of an ML model. For instance, one can use it as a toy dataset to investigate the capacity and output behavior of a deep neural network before testing it on real-world data.
PMC-SA (PMC Structured Abstracts) is a dataset of academic publications, used for the task of structured summarization.
The PointDenoisingBenchmark dataset features 28 different shapes, split into 18 training shapes and 10 test shapes.
A dataset for detecting specific text chunks and categories of political advertising in the Polish language. It contains 1,705 human-annotated tweets tagged with nine categories, which constitute campaigning under Polish electoral law.
A dataset that represents the online media landscape as perceived by an average US news consumer. The dataset contains 0.9M articles covering policy topics published between Jan. 2017 and Aug. 2019 by 18 news outlets representing the political spectrum. Each outlet is labeled by its political leaning derived using a systematic aggregation of eight data sources. The news dataset is balanced with respect to publication date and outlet popularity. POLUSA enables studying a variety of subjects, e.g., media effects and political partisanship.