https://github.com/MindSpore-paper-code-3/code2/tree/main/DDRNet
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
Papers with Code 아카이브
Real-Time Semantic Segmentation
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Semantic Segmentation is a computer vision task that involves assigning a semantic label to each pixel in an image. In Real-Time Semantic Segmentation, the goal is to perform this labeling quickly and accurately in real-time, allowing for the segmentation results to be used for tasks such as object recognition, scene understanding, and autonomous navigation.
<span style="color:grey; opacity: 0.6">( Image credit: TorchSeg )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MindSpore-paper-code-3/code3/tree/main/fastscnn
https://github.com/MindSpore-paper-code-3/code4/tree/main/hardnet
https://github.com/MindSpore-paper-code-3/code7/tree/main/fastscnn
https://github.com/MindSpore-paper-code-3/code8/tree/main/DDRNet
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
https://github.com/MindSpore-paper-code-3/code8/tree/main/E-NET
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
https://github.com/MindSpore-paper-code-3/code8/tree/main/fastscnn
https://github.com/NASA-NeMO-Net/NeMO-Net
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
https://github.com/NeuronDroid/GVSS-S.A.Drone
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/OpenFirework/pytorch_solov2
https://github.com/Osdel/ssnets
https://github.com/PRBonn/LiDAR-MOS
Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform
https://github.com/PRBonn/bonnet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/PaddlePaddle/PaddleClas
https://github.com/PaddlePaddle/PaddleDetection
https://github.com/Paultool/segnet
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/PhanTom2003/PSPnet
https://github.com/PingoLH/CenterNet-HarDNet
https://github.com/PingoLH/FCHarDNet
https://github.com/PuchatekwSzortach/voc_fcn
https://github.com/RajkumarPreetham/Road-scene-understanding
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/Rakeshpavan333/oct_dil
https://github.com/Rintarooo/PSPNet
https://github.com/RituYadav92/Image-segmentation
https://github.com/Rosie-Brigham/sesmeg
https://github.com/SSN15/Behavioral-Cloning--Implementaion-of-Autonomous-car-using-deep-learning
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/SharifElfouly/easy-model-zoo
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
https://github.com/ShigemichiMatsuzaki/MSPL
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/Shuai-Xie/BiSeNet-CCP
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
https://github.com/Shualite/SFNet.pytorch
https://github.com/Shun14/enet
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
https://github.com/ShunyuYao/blitznet_instance_segment
https://github.com/SkyWa7ch3r/ImageSegmentation
https://github.com/SkyWa7ch3r/SceneSegmentation
https://github.com/TejasBajania/Mtech_pro
https://github.com/TejasBajania/Mtech_thesis_project
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.