Papers with Code 아카이브
Scene Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 3
- 보존된 평가 기록
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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/keyEpoch/semen_seg-kd
https://github.com/kim-younghan/FEELVOS
FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation
https://github.com/kingcong/PSPNet
https://github.com/kini5gowda/ALBA-RL-for-VOS
https://github.com/kkhosla96/cs231n-project
https://github.com/kklemon/bgan-pytorch
https://github.com/krishnapalS/Human-Pose-Estimation-using-ShelfNet
https://github.com/kuangzijian/Flow-Based-Video-Matting
https://github.com/kukby/Mish-semantic-segmentation-pytorch
https://github.com/kulkarnikeerti/SegNet-Semantic-Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/kyungsu-lee-ksl/ash
https://github.com/l1997i/lim3d
On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDAR
https://github.com/l1997i/rapid_seg
On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDAR
https://github.com/lalithjets/domain-generalization-for-surgical-scene-graph
Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection
https://github.com/lastbasket/endo-4dgs
Learning How To Robustly Estimate Camera Pose in Endoscopic Videos
https://github.com/leemathew1998/GradientWeight
https://github.com/leemathew1998/RG
https://github.com/llmbev/talk2bev
Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving
https://github.com/logictensornetworks/logictensornetworks
Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image Interpretation
https://github.com/lojzezust/lars_evaluator
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark
https://github.com/louisfinner/him2sam
https://github.com/lpiccinelli-eth/unidepth
iDisc: Internal Discretization for Monocular Depth Estimation
https://github.com/lufan31/comprecap
https://github.com/lunaproject22/aar
Spatial-Temporal Transformer for Dynamic Scene Graph Generation
https://github.com/lvyufeng/MindSpore-GAN
https://github.com/lxtGH/GALD-DGCNet
Global Aggregation then Local Distribution in Fully Convolutional Networks
https://github.com/lxx1991/VS-ReID
https://github.com/m-serra/action-inference-for-video-prediction-benchmarking
https://github.com/manideep2510/eye-in-the-sky
https://github.com/manthanpatel2/Object-Detection-on-a-Frame
https://github.com/mattangus/fast-semantic-segmentation
https://github.com/mattgorb/cnn_bold5000
https://github.com/mayu-ot/rethinking-evs
https://github.com/mcg-nju/trace
https://github.com/mdt48/semantic-segmentation-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.