Superpixels
92 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Superpixels
Most implemented papers
COCO-Stuff: Thing and Stuff Classes in Context
nightrome/cocostuff
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CVPR 2018
To understand stuff and things in context we introduce COCO-Stuff, which augments all 164K images of the COCO 2017 dataset with pixel-wise annotations for 91 stuff classes.
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
yhlleo/DeepSegmentor
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ICCV 2015
In this paper we address three different computer vision tasks using a single basic architecture: depth prediction, surface normal estimation, and semantic labeling.
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
cheng-01037/Self-supervised-Fewshot-Medical-Image-Segmentation
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ECCV 2020
Few-shot semantic segmentation (FSS) has great potential for medical imaging applications.
Inner and Inter Label Propagation: Salient Object Detection in the Wild
For most natural images, some boundary superpixels serve as the background labels and the saliency of other superpixels are determined by ranking their similarities to the boundary labels based on an inner propagation scheme.
Learning to Segment Object Candidates
facebookresearch/deepmask
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NeurIPS 2015
Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of candidate proposals is then passed to an object classifier.
Superpixels: An Evaluation of the State-of-the-Art
As such, and due to their quick adoption in a wide range of applications, appropriate benchmarks are crucial for algorithm selection and comparison.
Non-Local Deep Features for Salient Object Detection
Saliency detection aims to highlight the most relevant objects in an image.
Superpixel Sampling Networks
NVlabs/ssn_superpixels
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ECCV 2018
Superpixels provide an efficient low/mid-level representation of image data, which greatly reduces the number of image primitives for subsequent vision tasks.
Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging
We present a superpixel-based strategy for segmenting skin lesion on dermoscopic images.
Let's take a Walk on Superpixels Graphs: Deformable Linear Objects Segmentation and Model Estimation
While robotic manipulation of rigid objects is quite straightforward, coping with deformable objects is an open issue.
