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 1551–1575 of 1723 papers

TitleStatusHype
Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering—0
Towards General Purpose Geometry-Preserving Single-View Depth Estimation—0
An Analysis of State-of-the-Art Models for Situated Interactive MultiModal Conversations (SIMMC)—0
Analyzing Semantic Segmentation Using Hybrid Human-Machine CRFs—0
When Neural Networks Using Different Sensors Create Similar Features—0
Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models—0
Towards holistic scene understanding: Semantic segmentation and beyond—0
Analogical Image Translation for Fog Generation—0
A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truth—0
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces—0
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction—0
Towards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data—0
From Real to Synthetic and Back: Synthesizing Training Data for Multi-Person Scene Understanding—0
Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery—0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents—0
Fusion Based Holistic Road Scene Understanding—0
FusionSAM: Latent Space driven Segment Anything Model for Multimodal Fusion and Segmentation—0
From Flight to Insight: Semantic 3D Reconstruction for Aerial Inspection via Gaussian Splatting and Language-Guided Segmentation—0
Future Does Matter: Boosting 3D Object Detection with Temporal Motion Estimation in Point Cloud Sequences—0
FroDO: From Detections to 3D Objects—0
Gaga: Group Any Gaussians via 3D-aware Memory Bank—0
GAGS: Granularity-Aware Feature Distillation for Language Gaussian Splatting—0
A model of saliency-based visual attention for rapid scene analysis—0
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning—0
FroDO: From Detections to 3D Objects—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