Semantic Segmentation
Semantic segmentation, or image segmentation, is the task of clustering parts of an image together which belong to the same object class. It is a form of pixel-level prediction because each pixel in an image is classified according to a category.
Some example benchmarks for this task are Cityscapes, PASCAL VOC and ADE20K. Models are usually evaluated with the Mean Intersection-Over-Union (Mean IoU) and Pixel Accuracy metrics.
( Image credit: CSAILVision )
Leaderboards
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Subtasks
Latest papers without code
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms
There has recently been great progress in automatic segmentation of medical images with deep learning algorithms.
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread
The proposed algorithm for the first time achieves competitive accuracy and high inference efficiency simultaneously with a single CPU thread.
IMAGE CLASSIFICATION SALIENT OBJECT DETECTION SEMANTIC SEGMENTATION
Learning to adapt class-specific features across domains for semantic segmentation
Recent advances in unsupervised domain adaptation have shown the effectiveness of adversarial training to adapt features across domains, endowing neural networks with the capability of being tested on a target domain without requiring any training annotations in this domain.
PatchPerPix for Instance Segmentation
To our knowledge, our method is the first non-iterative method that guarantees instances to be composed of learnt shape patches.
Joint Learning of Instance and Semantic Segmentation for Robotic Pick-and-Place with Heavy Occlusions in Clutter
We present joint learning of instance and semantic segmentation for visible and occluded region masks.
Breast lesion segmentation in ultrasound images with limited annotated data
Ultrasound (US) is one of the most commonly used imaging modalities in both diagnosis and surgical interventions due to its low-cost, safety, and non-invasive characteristic.
Instance Segmentation of Visible and Occluded Regions for Finding and Picking Target from a Pile of Objects
We present a robotic system for picking a target from a pile of objects that is capable of finding and grasping the target object by removing obstacles in the appropriate order.
IMAGE GENERATION INSTANCE SEGMENTATION SEMANTIC SEGMENTATION
BARNet: Bilinear Attention Network with Adaptive Receptive Field for Surgical Instrument Segmentation
For the scale variation, our adaptive receptive field module aggregates multi-scale features and automatically fuses them with different weights.
Gated Path Selection Network for Semantic Segmentation
Semantic segmentation is a challenging task that needs to handle large scale variations, deformations and different viewpoints.
Probabilistic 3D Multilabel Real-time Mapping for Multi-object Manipulation
Probabilistic 3D map has been applied to object segmentation with multiple camera viewpoints, however, conventional methods lack of real-time efficiency and functionality of multilabel object mapping.