…Robotic grasping requires a variety of computer vision tasks such as object detection, segmentation, grasp prediction, pick planning, etc. The proposed dataset contains 100,000 images and 25 different object types, and is split into 5 difficulties to evaluate object detection and segmentation model performance in different grasping scenarios We also propose a new layout-weighted performance metric alongside the dataset for evaluating object detection and segmentation performance in a manner that is more appropriate for robotic grasp applications This repository contains the first phase of MetaGraspNet benchmark dataset which includes detailed object detection, segmentation, layout annotations, and a script for layout-weighted performance metric
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A high-resolution semantic segmentation dataset with 50 validation and 100 test objects. Image resolution in BIG ranges from 2048×1600 to 5000×3600.
6 PAPERS • 1 BENCHMARK
A medical image segmentation challenge at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2017.
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The dataset contains a Video capsule endoscopy dataset for polyp segmentation.
3 PAPERS • 1 BENCHMARK
Based on the MVSEC dataset, we select some image-event pairs to evaluate the segmentation performance, namely MVSEC-SEG, which only serves as a test set.
8 PAPERS • 1 BENCHMARK
IDDA is a large scale, synthetic dataset for semantic segmentation with more than 100 different source visual domains.
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The MM-WHS 2017 dataset is a dataset for multi-modality whole heart segmentation. It provides 20 labeled and 40 unlabeled CT volumes, as well as 20 labeled and 40 unlabeled MR volumes.
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…It is a semantic segmentation benchmark dataset, for the diverse crops in the Central Valley region of California at 10m spatial resolution using a Google Earth Engine based robust image processing pipeline
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…For each sequence we provide multiple sets of images containing RGB, depth, class segmentation, instance segmentation, flow, and scene flow data.
33 PAPERS • 1 BENCHMARK
…All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation. Also available on Academic torrent, Link is here
73 PAPERS • 5 BENCHMARKS
Toronto-3D is a large-scale urban outdoor point cloud dataset acquired by an MLS system in Toronto, Canada for semantic segmentation.
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DeepFashion2 is a versatile benchmark of four tasks including clothes detection, pose estimation, segmentation, and retrieval.
30 PAPERS • 2 BENCHMARKS
Based on the DSEC dataset, we select some image-event pairs to evaluate the segmentation performance, namely DSEC-SEG, which only serves as a test set.
2 PAPERS • 1 BENCHMARK
…The development set includes reference diarization and speech segmentation and may be used for any purpose including system development or training.
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The Weakly Occluded Scene Text (WOST) dataset is a public dataset for scene text segmentation. It is used to generate pixel-level annotations in scene text images 1.
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EPIC-SOUNDS includes 78.4k categorised and 39.2k non-categorised segments of audible events and actions, distributed across 44 classes.
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…Each segment is annotated for the presence of 11 emotions (angry, neutral, fear, happy, sad, disappointed, bored, disgusted, excited, surprised, fear and other)
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PASCAL-5i is a dataset used to evaluate few-shot segmentation. The dataset is sub-divided into 4 folds each containing 5 classes.
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…For all frames the dataset provides 3d pose and shape ground truth, as well as other rich image annotations including human segmentation, body part localisation semantics, and temporal correspondences.
OpenForensics is a large-scale dataset posing a high level of challenges that is designed with face-wise rich annotations explicitly for face forgery detection and segmentation.
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…It provides segmentation maps with 33 classes: three for each finger, palm, person, and background.
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…These images are manually labelled and segmented according to a hierarchical taxonomy to train and evaluate object detection algorithms. The annotations are provided in COCO format.
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…The dataset is designed to do binary semantic segmentation of burned vs unburned areas.
…It includes nearly 10,000 segmentations of 100 categories in over 4,500 images that were taken by people with visual impairments.
…It covers a variety of road geometries including freeway basic segments, weaving segments, expressway merge/diverge segments, signalized intersections, stop-controlled intersections, and intersections
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CryoNuSeg is a fully annotated FS-derived cryosectioned and H&E-stained nuclei instance segmentation dataset.
…Each image is annotated with various low/high-level vision modalities, including semantic segmentation, depth, surface normals, intrinsic colors, and optical flow.
The Toulouse Road Network dataset describes patches of road maps from the city of Toulouse, represented both as spatial graphs G = (A, X) and as grayscale segmentation images. The semantic segmentation of each patch is represented as a 64 × 64 grayscale image. The dataset is generated starting from publicly available data from OpenStreetMap.
…Prediction Dataset, with up to 66,560 sequences containing 550,400 eye-images and respective gaze vectors, created to foster research in spatio-temporal gaze estimation and prediction approaches; and 2) Eye Segmentation Dataset, consisting of 200 sequences sampled at 5 Hz, with up to 29,500 images, of which 5% contain a semantic segmentation label, devised to encourage the use of temporal information to propagate labels
…High quality sparese instance segmentation labels.
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MOTFront provides photo-realistic RGB-D images with their corresponding instance segmentation masks, class labels, 2D & 3D bounding boxes, 3D geometry, 3D poses and camera parameters.
…The dataset is used for a hand segmentation task and its sim-to-real adaptation benchmark. Training, validation, and testing sets contain 150, 000, 6, 500, and 6, 500 images, respectively.
Since robust foreground/background separation and segmentation of cellular objects (i.e.
…fashion experts containing 27 main apparel categories, 19 apparel parts, 294 fine-grained attributes and their relationships; (2) a dataset with everyday and celebrity event fashion images annotated with segmentation
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The dataset published here is the largest, most diverse and consistent crack segmentation dataset constructed so far. It contains 9255 images that combine different smaller open source datasets.
…The images are labeled with different types of annotations such as segmentation labels, pose or 3D.
The PKLot dataset contains 12,417 images of parking lots and 695,899 images of parking spaces segmented from them, which were manually checked and labeled.
17 PAPERS • 1 BENCHMARK
Based on the DDD17 dataset, we select some image-event pairs to evaluate the segmentation performance, namely DDD17-SEG, which only serves as a test set.
The HRF dataset is a dataset for retinal vessel segmentation which comprises 45 images and is organized as 15 subsets.
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…All tables come from a subset of SegmentedTables dataset.
…We create it from MOVi dataset for amodal segmentation. The virtual camera is set to go around the scene, capturing about 24 consecutive frames.
…The task is not just to semantically segment objects but also to identify their motion status.
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…The data includes RGB, depth, foreground segmentations and full body skeletons. In this dataset, both the training and testing labels are noisy (from Kinect).
Indian Pines is a Hyperspectral image segmentation dataset. The input data consists of hyperspectral bands over a single landscape in Indiana, US, (Indian Pines data set) with 145×145 pixels.
78 PAPERS • 2 BENCHMARKS
The PAX-Ray++ dataset uses pseudo-labeled thorax CTs to enable the segmentation of anatomy in Chest X-Rays.
Minor Irrigation Structures Check-Dam Dataset is a public dataset annotated by domain experts using images from Google static map for instance segmentation and object detection tasks.
…The proposed dataset will allow proper evaluation of salient edges and semantic segmentation of images focusing on the street view perspective