https://github.com/AICPS/roadscene2vec
공식 코드roadscene2vec: A Tool for Extracting and Embedding Road Scene-Graphs
Papers with Code 아카이브
Scene Graph Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 7
- 보존된 평가 기록
- 31
A scene graph is a structured representation of an image, where nodes in a scene graph correspond to object bounding boxes with their object categories, and edges correspond to their pairwise relationships between objects. The task of Scene Graph Generation is to generate a visually-grounded scene graph that most accurately correlates with an image.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CYVincent/Scene-Graph-Transformer-CogTree
공식 코드CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation
https://github.com/Dong-JinKim/DenseRelationalCaptioning
공식 코드Dense Relational Image Captioning via Multi-task Triple-Stream Networks
https://github.com/IIGROUP/PUM
공식 코드Probabilistic Modeling of Semantic Ambiguity for Scene Graph Generation
https://github.com/Jingkang50/OpenPSG
공식 코드https://github.com/KaihuaTang/Scene-Graph-Benchmark.pytorch
공식 코드https://github.com/KanghoonYoon/torch-rasgg
공식 코드RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via Multi-Prototype Learning
https://github.com/Karim-53/SGG
공식 코드https://github.com/Kenneth-Wong/MMSceneGraph
공식 코드Topic Scene Graph Generation by Attention Distillation from Caption
https://github.com/Kenneth-Wong/het-eccv20
공식 코드Sketching Image Gist: Human-Mimetic Hierarchical Scene Graph Generation
https://github.com/MECLabTUDA/VoxelSceneGraph
공식 코드https://github.com/Scarecrow0/BGNN-SGG
공식 코드Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation
https://github.com/ShunChengWu/3DSSG
공식 코드SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
https://github.com/ShunChengWu/SceneGraphFusion
공식 코드SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences
https://github.com/Wayfear/Coacher
공식 코드Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration
https://github.com/Wq23333/DLL
공식 코드https://github.com/Yuqifan1117/CaCao
공식 코드Visually-Prompted Language Model for Fine-Grained Scene Graph Generation in an Open World
https://github.com/aa200647963/sgg-dhl
공식 코드Dual-branch Hybrid Learning Network for Unbiased Scene Graph Generation
https://github.com/alirezazareian/gbnet
공식 코드https://github.com/alirezazareian/vspnet
공식 코드https://github.com/andy20178/sgformer
공식 코드SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph Generation
https://github.com/ardamamur/egoexor
공식 코드EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding
https://github.com/bknyaz/sgg
공식 코드Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
https://github.com/boschresearch/relationfield
공식 코드https://github.com/bowen-upenn/scene_graph_commonsense
공식 코드Hierarchical Relationships: A New Perspective to Enhance Scene Graph Generation
https://github.com/chch1999/rtpb
공식 코드Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation
https://github.com/coldmanck/recovering-unbiased-scene-graphs
공식 코드https://github.com/columbia-ai-robotics/BusyBot
공식 코드BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment
https://github.com/docworlds/tsg-bench
공식 코드https://github.com/dongxingning/sha-gcl-for-sgg
공식 코드Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation
https://github.com/egeozsoy/4D-OR
공식 코드https://github.com/egeozsoy/LABRAD-OR
공식 코드LABRAD-OR: Lightweight Memory Scene Graphs for Accurate Bimodal Reasoning in Dynamic Operating Rooms
https://github.com/egeozsoy/LF-SGG
공식 코드https://github.com/egeozsoy/MM-OR
공식 코드https://github.com/egeozsoy/Oracle
공식 코드ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling
https://github.com/endlinc/llava-spacesgg
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.