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

Libraries

Use these libraries to find Real-time Instance Segmentation models and implementations
2 papers
28,588

Most implemented papers

YOLACT: Real-time Instance Segmentation

dbolya/yolact ICCV 2019

Then we produce instance masks by linearly combining the prototypes with the mask coefficients.

YOLACT++: Better Real-time Instance Segmentation

dbolya/yolact 3 Dec 2019

Then we produce instance masks by linearly combining the prototypes with the mask coefficients.

SOLOv2: Dynamic and Fast Instance Segmentation

WXinlong/SOLO 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.

RTMDet: An Empirical Study of Designing Real-Time Object Detectors

open-mmlab/mmdetection 14 Dec 2022

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.

BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation

aim-uofa/AdelaiDet 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.

CenterMask : Real-Time Anchor-Free Instance Segmentation

youngwanLEE/CenterMask 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

haotian-liu/yolact_edge 22 Dec 2020

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 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

torrvision/straighttoshapes 27 May 2019

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 ICCV 2019

In this paper, we propose a novel top-down instance segmentation framework based on explicit shape encoding, named \textbf{ESE-Seg}.