Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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First-person (egocentric) video dataset; multi-faceted non-scripted recordings in the wearers' homes, capturing all daily activities in the kitchen over multiple days. Annotations are collected using a novel live audio commentary approach.
We introduce VISOR, a new dataset of pixel annotations and a benchmark suite for segmenting hands and active objects in egocentric video. VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenges not encountered in current video segmentation datasets. Specifically, we need to ensure both short- and long-term consistency of pixel-level annotations as objects undergo transformative interactions, e.g. an onion is peeled, diced and cooked - where we aim to obtain accurate pixel-level annotations of the peel, onion pieces, chopping board, knife, pan, as well as the acting hands. VISOR introduces an annotation pipeline, AI-powered in parts, for scalability and quality. Data published under the Creative Commons Attribution-NonCommerial 4.0 International License.
kiyoonkim/EPIC-KITCHENS-100-trimmed dataset hosted on Hugging Face and contributed by the HF Datasets community
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
Motivation
The actual download link is very slow, including the academic torrent. Therefore, to spare fellow community members from this misery, I am uploading the dataset here.
Source
You can fnd the original source to download the dataset: https://github.com/epic-kitchens/epic-kitchens-download-scripts
Citation
@INPROCEEDINGS{Damen2018EPICKITCHENS, title={Scaling Egocentric Vision: The EPIC-KITCHENS Dataset}, author={Damen, Dima and Doughty, Hazel and… See the full description on the dataset page: https://huggingface.co/datasets/awsaf49/epic_kitchens_100.
http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/
EPIC-KITCHENS-100: Extended Footage for EPIC-KITCHENS dataset, to 100 hours of footage. 10.5523/bris.2g1n6qdydwa9u22shpxqzp0t8m 2020-09-10 N.b. please also see ERRATUM published at 2021-05-25 This supersedes the original torrent, which had a small change made.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
EPIC-KITCHENS-100 is a large-scale dataset in first-person (egocentric) vision; multi-faceted, audio-visual, non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities in the kitchen over multiple days. Annotations are collected using a novel 'Pause-and-Talk' narration interface.
EPIC-KITCHENS-100 is an extension of the EPIC-KITCHENS dataset released in 2018, to 100 hours of footage.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
The EPIC-KITCHENS-55 dataset comprises a set of 432 egocentric videos recorded by 32 participants in their kitchens at 60fps with a head mounted camera. There is no guiding script for the participants who freely perform activities in kitchens related to cooking, food preparation or washing up among others. Each video is split into short action segments (mean duration is 3.7s) with specific start and end times and a verb and noun annotation describing the action (e.g. ‘open fridge‘). The verb classes are 125 and the noun classes 331. The dataset is divided into one train and two test splits.
Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
📙 Overview
EPIC-Kitchen-100 video features extracted by VideoMAE_L14 at 8 fps. It is used for evaluating the video-text retrieval ability of EgoInstructor. It contains 700 files, each file (e.g. P01_01.pth.tar) is a TxD feature vector, where T refers to the length of the video and D is 768.
🏋️ How-To-Use
Please refer to code EgoInstructor for details.
🎓 Citation
@article{xu2024retrieval, title={Retrieval-augmented egocentric video captioning}, author={Xu… See the full description on the dataset page: https://huggingface.co/datasets/Jazzcharles/epic_kitchen_videomae_L14_feature_fps8.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This material is part of the free Environmental Performance in Construction (EPiC) Database. The EPiC Database contains embodied environmental flow coefficients for 250+ construction materials using a comprehensive hybrid life cycle inventory approach.Steel is a ferrous metal and is an alloy of iron and carbon, as well as potential other elements. It has a very high tensile strength. Steel has been used in the construction industry for over a century. Stainless steel is extremely resistant to corrosion.The core material for making steel is iron, which is found in iron ore. Iron is extracted from iron ore in blast furnaces through the smelting process, while controlling for the content of carbon. To render the steel stainless, chromium is needed and is typically added as stainless steel scraps. The molten steel is usually further processed before being cast for its final use.Steel is commonly used in the construction industry, mainly as a structural material. Stainless steel sheets are used to produce a range of finishing materials, such as high durability cladding, roofing (mainly for airports), and kitchen surfaces.
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Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
First-person (egocentric) video dataset; multi-faceted non-scripted recordings in the wearers' homes, capturing all daily activities in the kitchen over multiple days. Annotations are collected using a novel live audio commentary approach.