Real-time Instance Segmentation
22 papers with code • 6 benchmarks • 5 datasets
Similar to its parent task, instance segmentation, but with the goal of achieving real-time capabilities under a defined setting.
Image Credit: SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation
Benchmarks
These leaderboards are used to track progress in Real-time Instance Segmentation
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Libraries
Use these libraries to find Real-time Instance Segmentation models and implementations
MS COCO
Cityscapes
KITTI
MSCOCO
MEIS
Most implemented papers
YOLACT: Real-time Instance Segmentation
Then we produce instance masks by linearly combining the prototypes with the mask coefficients.
YOLACT++: Better Real-time Instance Segmentation
dbolya/yolact
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Then we produce instance masks by linearly combining the prototypes with the mask coefficients.
SOLOv2: Dynamic and Fast Instance Segmentation
WXinlong/SOLO
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NeurIPS 2020
Importantly, we take one step further by dynamically learning the mask head of the object segmenter such that the mask head is conditioned on the location.
BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation
aim-uofa/AdelaiDet
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CVPR 2020
The proposed BlendMask can effectively predict dense per-pixel position-sensitive instance features with very few channels, and learn attention maps for each instance with merely one convolution layer, thus being fast in inference.
RTMDet: An Empirical Study of Designing Real-Time Object Detectors
In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO series and is easily extensible for many object recognition tasks such as instance segmentation and rotated object detection.
CenterMask : Real-Time Anchor-Free Instance Segmentation
youngwanLEE/CenterMask
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arXiv 2019
We hope that CenterMask and VoVNetV2 can serve as a solid baseline of real-time instance segmentation and backbone network for various vision tasks, respectively.
YolactEdge: Real-time Instance Segmentation on the Edge
We propose YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
Sparse Instance Activation for Real-Time Instance Segmentation
hustvl/sparseinst
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CVPR 2022
In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation.
Straight to Shapes++: Real-time Instance Segmentation Made More Accurate
The STS model can run at 35 FPS on a high-end desktop, but its accuracy is significantly worse than that of offline state-of-the-art methods.
Explicit Shape Encoding for Real-Time Instance Segmentation
WenqiangX/ese_seg
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ICCV 2019
In this paper, we propose a novel top-down instance segmentation framework based on explicit shape encoding, named \textbf{ESE-Seg}.
