Lyft-Perception-Challenge
Image segmentation model
This project aims to accurately detect vehicles and drivable roads in images from a simulator at high frame rates.
Won 28th place in this competition to accurately detect cars and road in images from CARLA simulator at 10 frames per second.
9 stars
1 watching
0 forks
Language: Python
last commit: about 2 years ago
Linked from 1 awesome list
convolutional-neural-networkslyft-perception-challengesegmentationudacity-self-driving-car
amin-tgz/awesome-carlaRelated projects:
| Repository | Description | Stars |
|---|---|---|
 henyau/image-segmentation-with-unet | Automated image segmentation of road and vehicle features from video data using the U-Net algorithm | 15 |
 evanwy/carlasemseg | Automated image segmentation algorithm for autonomous driving research using the Carla dataset | 8 |
 preritj/segmentation | Deep learning models for semantic segmentation of images | 101 |
 fregu856/segmentation | An implementation of the ENet model for semantic segmentation in images, trained on the Cityscapes dataset. | 245 |
 marvinteichmann/kittiseg | An implementation of a fully convolutional network-based road segmentation model using TensorFlow. | 911 |
 lironui/abcnet | Develops an efficient network architecture for semantic segmentation of high-resolution remote sensing images. | 34 |
 enginbozkurt/carlasimulatordatacollector | Automates data collection from the CARLA simulator for use in semantic segmentation training. | 26 |
 zhengpeng7/birefnet | An open-source implementation of an image segmentation model that combines background removal and object detection capabilities. | 1,484 |
 tobypde/frrn | A software framework for training and evaluating full-resolution residual networks for semantic image segmentation tasks | 280 |
 uber-research/upsnet | Develops an instance segmentation and panoptic segmentation model for computer vision tasks. | 648 |
 s-nandi/carla-car-detection | An application of object detection to simulate traffic signs/lights and cars in the Carla simulator environment | 5 |
 speedinghzl/ccnet | An implementation of a deep learning model for semantic segmentation using a novel attention mechanism to capture long-range dependencies in images. | 1,432 |
 fabianbormann/tensorflow-deconvnet-segmentation | An implementation of a deep learning algorithm for image segmentation using convolutional neural networks | 220 |
 linksense/lightnet | Research into efficient neural networks for semantic image segmentation in autonomous driving applications | 719 |
 simonkohl/probabilistic_unet | Reimplementation of a neural network model for conditional segmentation of ambiguous images | 548 |