SOTAVerified

Scene Understanding

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.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1451–1475 of 1723 papers

TitleStatusHype
Assessing the generalization performance of SAM for ureteroscopy scene understanding—0
A Sentence Is Worth a Thousand Pixels—0
A Semantic Communication System for Real-time 3D Reconstruction Tasks—0
Str-L Pose: Integrating Point and Structured Line for Relative Pose Estimation in Dual-Graph—0
Semantic and structural image segmentation for prosthetic vision—0
Structural Concept Learning via Graph Attention for Multi-Level Rearrangement Planning—0
You Only Speak Once to See—0
Structured agents for physical construction—0
Artifacts Mapping: Multi-Modal Semantic Mapping for Object Detection and 3D Localization—0
Structured Generative Models for Scene Understanding—0
Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning—0
Neural Language of Thought Models—0
A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation—0
Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos—0
Submodular Field Grammars: Representation, Inference, and Application to Image Parsing—0
A Robotic 3D Perception System for Operating Room Environment Awareness—0
SUN RGB-D: A RGB-D Scene Understanding Benchmark Suite—0
SUPER: A Novel Lane Detection System—0
ArK: Augmented Reality with Knowledge Interactive Emergent Ability—0
SuperGSeg: Open-Vocabulary 3D Segmentation with Structured Super-Gaussians—0
Weakly Supervised Learning of Affordances—0
Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review—0
SurgiSAM2: Fine-tuning a foundational model for surgical video anatomy segmentation and detection—0
SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks—0
Argus: Leveraging Multiview Images for Improved 3-D Scene Understanding With Large Language Models—0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified