…By collecting data in simulations, multi-modal sensor data and precise ground truth labels are obtainable such as the RGB image, depth image, semantic segmentation, change segmentation, camera poses, and
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…lyrics encode an important part of the semantics of a song, the authors focus on the description of the methods they proposed to extract relevant information from the lyrics, such as their structure segmentation can be exploited by music search engines and music professionals (e.g. journalists, radio presenters) to better handle large collections of lyrics, allowing an intelligent browsing, categorization and segmentation
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…Basically, "rationales" are segments of the text that support an annotator's classification. Then the rationales would be segments of the text that support the claim (by an annotator) that the review is, indeed, positive. Here are some examples of positive rationales (the segments enclosed by double square brackets): [[you will enjoy the hell out of]] American Pie. fortunately, they [[managed to do it in an interesting
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Introduced by Da et al. in DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System Grand-Challenge Page 1. Colonoscopy tissue segment dataset Colonoscopy pathology examination can find cells of early-stage colon tumor from small tissue slices. Here we propose a challenge task on automatic colonoscopy tissue segmentation and screening, aiming at automatic lesion segmentation and classification of the whole tissue (benign vs. malignant). DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System[J]. Medical Image Analysis, 2022: 102485.
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…Leaf wood labels were transferred from contemporaneous (2021) TLS acquisition, for which segmentation was done using LeWoS and onscreen post correction.
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…Each segment is annotated for the presence of 9 emotions (angry, excited, fear, sad, surprised, frustrated, happy, disappointed and neutral) as well as valence, arousal and dominance.
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…Note that this implies TAO-Amodal also includes modal segmentation masks (as visualized in the color overlays above).
…It's provided as a large-scale benchmark for food image segmentation.
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…Two sets: ModelNet-C for point cloud classification and ShapeNet-C for part segmentation. Real-world corruption sources, ranging from object-, senor-, and processing-levels.
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…images/raw_scale001-raw_scale0075) 11,280 images of the raw sensor data processed through twelve different pipelines (microscopy/images/processed_views) Raw-Drone: 548 raw drone camera images for car segmentation (drone/images_tiles_256/raw_scale100) with corresponding binary segmentation mask (drone/masks_tiles_256).
The Sunnybrook Cardiac Data (SCD), also known as the 2009 Cardiac MR Left Ventricle Segmentation Challenge data, consist of 45 cine-MRI images from a mixed of patients and pathologies: healthy, hypertrophy Subset of this data set was first used in the automated myocardium segmentation challenge from short-axis MRI, held by a MICCAI workshop in 2009.
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…Several methods have been developed to automate polyp detection and segmentation. To our knowledge, this is the most comprehensive detection and pixel-level segmentation dataset (referred to as PolypGen) curated by a team of computational scientists and expert gastroenterologists.
…It contains over 10M segments of multilingual open data. The data has been collected from sites allowing free use and reuse of its content, as well as from Public Sector web sites.
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…To validate our approach we employ two popular video object segmentation datasets, DAVIS16 [38] and DAVIS17 [42]. For the multiple object video segmentation task we consider DAVIS17. As our goal is to segment objects in videos using language specifications, we augment all objects annotated with mask labels in DAVIS16 and DAVIS17 with non-ambiguous referring expressions. (We actually quantified that only∼ 15% of the collected descriptions become invalid over time and it does not affect strongly segmentation results as temporal consistency step helps to disambiguate some We believe the collected data will be of interest to segmentation as well as vision and language communities, providing an opportunity to explore language as alternative input for video object segmentation
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…The dataset collects valuable contents from public perception dataset Waymo Open Dataset and provides lane&closest-in-path object(CIPO) annotation for 1000 segments.
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…It contains human annotated ground truth labels for both bounding boxes and instance-wise segmentation masks.
…Each image has high-quality segmentation mask, sketch, descriptive text, and image with transparent background.
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…In addition to the samples themselves, some entries in the dataset are accompanied by supplementary natural language descriptions, size measurements, and segmentation masks.
…To gather the simulated dataset, we captured before and after flood pairs from 2000 viewpoints with the following modalities: non-flooded RGB image, depth map, segmentation map flooded RGB image, binary mask of the flooded area, segmentation map The camera was placed about 1.5 above ground, and has a field of view of 120 degree, and the resolution of the images is 1200 x 900.
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…The dataset consists of short speech segments automatically extracted from media videos available on YouTube and manually transcribed, with some pre- and post-processing.
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…The dataset comprises Computed Tomography (CT), Positron Emission Tomography (PET)/CT images, semantic annotations of the tumors as observed on the medical images using a controlled vocabulary, segmentation
…This dataset consists in 4,000 English segments (4,500 tokens) that have been translated into each of 26 low-resource languages, as well as three higher-resource pivot languages (es, fr, hi).
The LIB-HSI dataset was created to develop deep learning methods for segmenting building facade materials. The images were captured using a Specim IQ hyperspectral camera.
…Annotations include: Multiple POS tags, morphological features and lemmatization Sentence segmentation and rough speech act Document structure in TEI XML (paragraphs, headings, figures, etc.)
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The SegmentedTables dataset is a collection of almost 2,000 tables extracted from 352 machine learning papers. Each table consists of rich text content, layout and caption.
We present YTSeg, a topically and structurally diverse benchmark for the text segmentation task based on YouTube transcriptions.
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…The data for each image includes segmentation maps, 3d depth maps, and normal maps of of the liquid or object inside the transparent vessel, and the vessel.
Automated leaf segmentation is a challenging area in computer vision.
…The dataset is segmented in 3 different subsets, each corresponding to a severity level of the LaTeXML software responsible for the HTML5 conversion.
This dataset can be used to develop novel Image segmentation techniques and ML based techniques for vision.
…The dataset consists of video retrieval, moment retrieval, and two novel moment segmentation and step captioning tasks.
…The datasets contains 6,892 segment-level summarization instances for training and evaluating of performance.
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Camouflaged Object (CAMO) dataset specifically designed for the task of camouflaged object segmentation.
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This dataset contains a large number of segmented nuclei images. Within this folder are two subfolders: images contains the image file. masks contains the segmented masks of each nucleus. This folder is only included in the training set.
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…This dataset can also be used for other learning use-cases, like instance segmentation or depth estimation. Or where household objects or continual learning are of interest. In addition, we also provide a corresponding depth, segmentation, and normal image. In addition to the RGB, depth, segmentation, and normal images, we also provide the calculated features of the RGB images (by ResNet50) as used in our RECALL paper.
…The FMB dataset includes rich scenes under different illumination conditions, so that it enables fusion/segmentation model to improve the generalization ability greatly.
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…The goal of this work is to segment the sections of clinical medical domain documentation.
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…A subset of 1.9M includes diverse annotations types. 15,851,536 boxes on 600 classes 2,785,498 instance segmentations on 350 classes 3,284,280 relationship annotations on 1,466 relationships 675,155
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…Segments of each song are annotated as “voice” (sung or spoken) or “no-voice”. The songs constitute a total of about 6 hours of music.
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…Possible applications include but are not limited to semantic segmentation, object detection and object counting. The corresponding ground-truth labels were generated through a hybrid approach involving semi-automatic and manual semantic segmentation.
The dataset comes with a shot segmentation (around 1 million shots) for which we analyze content specifics and statistics.
…It consists of 29 time-lapse image sequences with various annotations (pixel-wise segmentation masks, object-wise bounding boxes, and tracking information), made publicly available to the scientific community
…The dataset also provides image segmentation masks, which labels persuasion strategies in the corresponding ad images on the test split.
…low number of target pixels (RFI) proportional to the total data volume makes this dataset a useful test for RFI detection schemes in radio astronomy and, more generally, anomaly detection or semantic segmentation
The LIVECell (Label-free In Vitro image Examples of Cells) dataset is a large-scale microscopic image dataset for instance-segmentation of individual cells in 2D cell cultures.
A dataset of 100K synthetic images of skin lesions, ground-truth (GT) segmentations of lesions and healthy skin, GT segmentations of seven body parts (head, torso, hips, legs, feet, arms and hands), and
…It is restricted to a subset of four out of the total 23 categories -- politics, society, economics and science -- and contains additional annotations. 3 human annotators familiar with linguistics segmented
…With a median number of 5 experts scoring every EEG segment, MODA offers sleep spindle annotations of a quality unseen in previous datasets.