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 1301–1325 of 1723 papers

TitleStatusHype
Towards Scene Understanding: Unsupervised Monocular Depth Estimation With Semantic-Aware Representation—0
Towards Scene Understanding with Detailed 3D Object Representations—0
Towards seamless multi-view scene analysis from satellite to street-level—0
Towards Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations—0
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation—0
Towards urban scenes understanding through polarization cues—0
Training-Free Model Merging for Multi-target Domain Adaptation—0
TransforMerger: Transformer-based Voice-Gesture Fusion for Robust Human-Robot Communication—0
Transformers for Image-Goal Navigation—0
TraveLLaMA: Facilitating Multi-modal Large Language Models to Understand Urban Scenes and Provide Travel Assistance—0
TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission System—0
Two Stream Scene Understanding on Graph Embedding—0
U4D: Unsupervised 4D Dynamic Scene Understanding—0
RemoteNet: Remote Sensing Image Segmentation Network based on Global-Local Information—0
Understanding and Evaluating Hallucinations in 3D Visual Language Models—0
Understanding Bayesian Rooms Using Composite 3D Object Models—0
Understanding Indoor Scenes Using 3D Geometric Phrases—0
Understanding Pedestrian Behaviors From Stationary Crowd Groups—0
Understanding Real World Indoor Scenes With Synthetic Data—0
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks—0
Underwater Diffusion Attention Network with Contrastive Language-Image Joint Learning for Underwater Image Enhancement—0
Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs—0
Unified Representation Space for 3D Visual Grounding—0
Unified Scene Representation and Reconstruction for 3D Large Language Models—0
Uni-Fusion: Universal Continuous Mapping—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