Papers with Code 아카이브

Scene Parsing

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 9
평가표: 2
보존된 평가 기록: 3

Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ywcmaike/TianchiVideoCharacterSegmentationPreliminary

Video Object Segmentation using Space-Time Memory Networks

https://github.com/zacharie12/zacharie

Learning to Compose Dynamic Tree Structures for Visual Contexts

https://github.com/zawlin/cvpr17_vtranse

Visual Translation Embedding Network for Visual Relation Detection

https://github.com/zh320/realtime-semantic-segmentation-pytorch

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/zhang-tao-whu/DVIS

DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries

https://github.com/zhaominyiz/c3-stisr

Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution

https://github.com/zhihaozhang97/ru-ai

Microsoft COCO: Common Objects in Context

https://github.com/zhiqwang/crnn.pytorch

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zhiqwang/image-captioning

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zhouxian/FluidLab

Diffusion-based Generation, Optimization, and Planning in 3D Scenes

https://github.com/zhucheng725/MobileNetv1_Segnet_keras_tensorrt

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/zhuotongchen/self-healing-robust-neural-networks-via-closed-loop-control

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/zixuan-chen/M3VOS_Experiment

M$^3$-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation

https://github.com/zj603252818/FCN8s

Fully Convolutional Networks for Semantic Segmentation

https://github.com/zju-vipa/KamalEngine

Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More

https://github.com/zkyntu/UnLanedet

Spatial As Deep: Spatial CNN for Traffic Scene Understanding

https://github.com/zkyseu/PPlanedet

Spatial As Deep: Spatial CNN for Traffic Scene Understanding

https://github.com/zlw9161/carrada-rac

Multi-View Radar Semantic Segmentation

https://github.com/zlw9161/pkc

Multi-View Radar Semantic Segmentation

https://github.com/ztoString/CRNN_CTC_OCR_TensorFlow

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zuosc19/gaussianworld

EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene Understanding

https://github.com/zwenwang/CTPN_Pytorch

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zyasjtu/CNN-RNN-CTC

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

https://github.com/zzy-zhou/renet

Event-Free Moving Object Segmentation from Moving Ego Vehicle

https://gitlab.com/Percipiote/skelda

Microsoft COCO: Common Objects in Context

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.