Papers with Code 아카이브

Scene Understanding

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하위 태스크: 6
평가표: 3
보존된 평가 기록: 5

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

코드

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

https://github.com/feevos/resuneta

ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

https://github.com/feibryantkit/lf-tracy

OAFuser: Towards Omni-Aperture Fusion for Light Field Semantic Segmentation

https://github.com/feinanshan/TDNet

Temporally Distributed Networks for Fast Video Semantic Segmentation

https://github.com/fenglian425/Agriculture_AI

Pyramid Scene Parsing Network

https://github.com/fiveai/saod

One Metric to Measure them All: Localisation Recall Precision (LRP) for Evaluating Visual Detection Tasks

https://github.com/fkluger/tchl

Temporally Consistent Horizon Lines

https://github.com/flyreelai/sslayout360

SSLayout360: Semi-Supervised Indoor Layout Estimation from 360-Degree Panorama

https://github.com/fmahoudeau/ShelfNet-Human-Pose-Estimation

ShelfNet for Fast Semantic Segmentation

https://github.com/fmahoudeau/fcn

Fully Convolutional Networks for Semantic Segmentation

https://github.com/foolwood/SiamMask

SiamMask: A Framework for Fast Online Object Tracking and Segmentation

https://github.com/fourmi1995/IronSegExperiment-LinkNet

LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

https://github.com/fudan-zvg/DGMN2_MindSpore_Ascend

Dynamic Graph Message Passing Networks for Visual Recognition

https://github.com/fzi-forschungszentrum-informatik/mrf

SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth

https://github.com/gaelmoccand/RoadSegmentation_CNN

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

https://github.com/ganwanshui/simpleoccupancy

SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving

https://github.com/geekswaroop/Human-Parsing

Pyramid Scene Parsing Network

https://github.com/geodekid/FCN

Fully Convolutional Networks for Semantic Segmentation

https://github.com/gfoxx29/Image-Captioning

Microsoft COCO: Common Objects in Context

https://github.com/gjp1203/LIV360SV

The Cityscapes Dataset for Semantic Urban Scene Understanding

https://github.com/google-research/deeplab2

Waymo Open Dataset: Panoramic Video Panoptic Segmentation

https://github.com/griffbr/ODMD

Learning Object Depth from Camera Motion and Video Object Segmentation

https://github.com/griffbr/VOSVS

Tukey-Inspired Video Object Segmentation

https://github.com/guanfuchen/video_obj

Fast and Accurate Online Video Object Segmentation via Tracking Parts

https://github.com/gunpowder78/PReMVOS

PReMVOS: Proposal-generation, Refinement and Merging for Video Object Segmentation

https://github.com/happytianhao/tade

CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving

https://github.com/harryhan618/SCNN_Pytorch

Spatial As Deep: Spatial CNN for Traffic Scene Understanding

https://github.com/harryhan618/scnn

Spatial As Deep: Spatial CNN for Traffic Scene Understanding

https://github.com/hav4ik/Hydra

Multi-Task Learning as Multi-Objective Optimization

https://github.com/hgjeon/CarND-Semantic-Segmentation

Fully Convolutional Networks for Semantic Segmentation

https://github.com/hkchengrex/Mask-Propagation

Video Object Segmentation using Space-Time Memory Networks

https://github.com/hkchengrex/Scribble-to-Mask

Modular Interactive Video Object Segmentation: Interaction-to-Mask, Propagation and Difference-Aware Fusion

https://github.com/hmi88/what

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

https://github.com/hoidn/ptychopinn

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

https://github.com/holyseven/PSPNet-TF-Reproduce

Pyramid Scene Parsing Network

https://github.com/hosshonarvar/Image-Segmentation

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

https://github.com/huggingface/transformers

Mask2Former for Video Instance Segmentation

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