adaptis
Instance selector
An instance segmentation network that adapts to varying object densities and complexities
[ICCV19] AdaptIS: Adaptive Instance Selection Network, https://arxiv.org/abs/1909.07829
336 stars
24 watching
32 forks
Language: Jupyter Notebook
last commit: almost 4 years ago
Linked from 1 awesome list
adaptiscityscapesinstance-segmentationmapillary-vistas-datasetms-cocomxnetpanoptic-segmentationpytorch
mrgloom/awesome-semantic-segmentationRelated projects:
| Repository | Description | Stars |
|---|---|---|
 msracver/fcis | An implementation of a fully convolutional instance-aware semantic segmentation framework using CUDA. | 1,567 |
 wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 851 |
 liyxi/adaptnas | An approach to improve neural architecture search by adapting architectures between domains to improve generalization performance on new datasets. | 7 |
 daijifeng001/mnc | An instance-aware semantic segmentation system based on deep convolutional networks using multi-task network cascades. | 489 |
 kuangjuihsu/deepco3 | A deep learning framework for instance co-segmentation and object colocalization | 137 |
 jackiezhangdx/instancesegmentationlist | Compiles and organizes state-of-the-art instance segmentation papers and resources | 88 |
 wxinlong/solo | An implementation of instance segmentation algorithms using PyTorch. | 1,714 |
 jp-liu/fit-screen | A utility library for creating adaptive screens in web applications that support multiple frameworks and don't require bundling. | 72 |
 zieiony/materialrecents | An Android adapter container for displaying a list of items with various customization options | 494 |
 pngwn/svelte-adaptive-sensors | A library that provides device and network information to inform adaptive app behavior | 50 |
 hciilab/derpn | Improves object detection by generating region proposals with increased adaptivity. | 156 |
 youngwanlee/centermask | An efficient anchor-free instance segmentation system with a novel spatial attention-guided mask branch and an improved backbone network | 774 |
 imatge-upc/saliency-2016-cvpr | This project proposes a solution to predict salient areas in images using convolutional neural networks. | 186 |
 bbn-q/adapt | A package that adapts sampling methods to optimize parameter space exploration based on observed data information content. | 8 |
 gothicai/instaboost | Implementation of instance segmentation via probability map guided copy-pasting | 399 |