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 1626–1650 of 1723 papers

TitleStatusHype
HAECcity: Open-Vocabulary Scene Understanding of City-Scale Point Clouds with Superpoint Graph Clustering—0
FastLGS: Speeding up Language Embedded Gaussians with Feature Grid Mapping—0
Hallucinated Humans as the Hidden Context for Labeling 3D Scenes—0
HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning—0
Handling Geometric Domain Shifts in Semantic Segmentation of Surgical RGB and Hyperspectral Images—0
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding—0
Transavs: End-To-End Audio-Visual Segmentation With Transformer—0
HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors—0
Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes—0
Towards seamless multi-view scene analysis from satellite to street-level—0
Hierarchical Scene Parsing by Weakly Supervised Learning with Image Descriptions—0
Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image—0
Towards Trustworthy Automated Driving through Qualitative Scene Understanding and Explanations—0
Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction—0
High-Accuracy Facial Depth Models derived from 3D Synthetic Data—0
Highway Driving Dataset for Semantic Video Segmentation—0
Factor Graph based 3D Multi-Object Tracking in Point Clouds—0
HIS-GPT: Towards 3D Human-In-Scene Multimodal Understanding—0
Factored Neural Representation for Scene Understanding—0
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation—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