Animal Kingdom is a large and diverse dataset that provides multiple annotated tasks to enable a more thorough understanding of natural animal behaviors. The wild animal footage used in the dataset records different times of the day in an extensive range of environments containing variations in backgrounds, viewpoints, illumination and weather conditions. More specifically, the dataset contains 50 hours of annotated videos to localize relevant animal behavior segments in long videos for the video grounding task, 30K video sequences for the fine-grained multi-label action recognition task, and 33K frames for the pose estimation task, which correspond to a diverse range of animals with 850 species across 6 major animal classes.

The Safety of street animals is a critical issue as it highlights the importance of technology in human-animal interaction. This dataset highlights the significance of understanding and enhancing the safety of street animals through the lens of machine learning applications, particularly focusing on using night vision images to detect and identify these animals in urban environments. This study aims to contribute to developing innovative technologies that can improve the detection and monitoring of animals, thereby reducing the risk of accidents and enhancing their safety.

Animals with Attributes 2 (AwA2) is a dataset for benchmarking transfer-learning algorithms, such as attribute base classification and zero-shot learning. AwA2 is a drop-in replacement of original Animals with Attributes (AwA) dataset, with more images released for each category. Specifically, AwA2 consists of in total 37322 images distributed in 50 animal categories. The AwA2 also provides a category-attribute matrix, which contains an 85-dim attribute vector (e.g., color, stripe, furry, size, and habitat) for each category.

Various species have been tracked using ARGOS PTT trackers since the early 1990's. These include Emperor, King and Adelie pengiuns, Light-mantled Sooty, Grey-headed and Black-browed albatrosses, Antarctic and Australian fur seals, Southern Elephant Seal and Blue and Humpback whales. Note that not all data for any species or locations is or will be exposed to OBIS. Geographic coverage is from Heard Island to the west and Macquarie Island to the east and several islands near the southern end of Chile. The data has been filtered to remove most but not all erroneous positions.

Dataset

This dataset was created by JUNYAO ZHANG

Contents

Animals are multicellular eukaryotic organisms in the biological kingdom Animalia ˌ æ n ɪ ˈ m eɪ l i ə With few exceptio

AiBototicus/Animals dataset hosted on Hugging Face and contributed by the HF Datasets community

The nine (moving camera) videos in this benchmark exhibit camouflaged animals that are difficult to see in a single frame, but can be detected based upon their motion across frames.

This is a test dataset of animals and names that the owner wishes were common. This is only a test.

A sub-dataset of animals currently in the shelter, sorted by type and Intake Date. This provides a way for owners to check the shelter for lost pets, or a way for prospective owners to find new pets.

Imports of Live Animals Sitc in the United States increased to 370 USD Million in February from 324 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports of Live Animals Sitc.

It comprises synthetic mesh sequences from Deformation Transfer for Triangle Meshes.

Explore the statistics for Pets & Animals eCommerce in 2024, including store count by region and platform, estimated sales amount by platform and region, products sold by platform and region, and total app spend by platform and region. Gain insights into regional preferences, market penetration, consumer trends, and technological investments within the Pets & Animals sector. Discover the leading regions and platforms, as well as the dynamics of sales and product volumes. Stay informed about the evolving landscape of Pets & Animals online stores for a comprehensive understanding of the market.

This statistic displays the number of animals used in scientific research in the European Union (and Norway) in 2022, by class of animal. In that year, around four million mice were used in scientific research in the EU, while around 626 thousand rats were used.

Mexico Imports: Live Animals & Animal Products (LP) data was reported at 192.055 USD mn in 2017. This records an increase from the previous number of 185.369 USD mn for 2016. Mexico Imports: Live Animals & Animal Products (LP) data is updated yearly, averaging 186.976 USD mn from Dec 2012 (Median) to 2017, with 6 observations. The data reached an all-time high of 192.055 USD mn in 2017 and a record low of 64.780 USD mn in 2012. Mexico Imports: Live Animals & Animal Products (LP) data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.JA017: Imports: China.

Mexico Imports: Live Animals: Bovine Animals data was reported at 4.951 USD mn in Feb 2019. This records an increase from the previous number of 2.686 USD mn for Jan 2019. Mexico Imports: Live Animals: Bovine Animals data is updated monthly, averaging 4.837 USD mn from Jan 1993 (Median) to Feb 2019, with 314 observations. The data reached an all-time high of 32.593 USD mn in May 2008 and a record low of 0.000 USD mn in Jan 2006. Mexico Imports: Live Animals: Bovine Animals data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.JA011: Imports: by Commodities.

We present the first method to perform automatic 3D pose, shape and texture capture of animals from images acquired in-the-wild. In particular, we focus on the problem of capturing 3D information about Grevy's zebras from a collection of images. We integrate the recent SMAL animal model into a network-based regression pipeline, which we train end-to-end on synthetically generated images with pose, shape, and background variation. We couple 3D pose and shape prediction with the task of texture synthesis, obtaining a full texture map of the animal from a single image. The predicted texture map allows a novel per-instance unsupervised optimization over the network features. We called the method SMALST (SMAL with learned Shape and Texture).

Georgia Imports of Live animals was US$62.46 Million during 2023, according to the United Nations COMTRADE database on international trade. Georgia Imports of Live animals - data, historical chart and statistics - was last updated on November of 2024.