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

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Showing 261–270 of 1723 papers

TitleStatusHype
HUSH: Holistic Panoramic 3D Scene Understanding using Spherical Harmonics—0
GroundingFace: Fine-grained Face Understanding via Pixel Grounding Multimodal Large Language Model—0
3D-MVP: 3D Multiview Pretraining for Manipulation—0
Beyond Human Perception: Understanding Multi-Object World from Monocular ViewCode0
Object-aware Sound Source Localization via Audio-Visual Scene UnderstandingCode0
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual LearningCode0
All-Day Multi-Camera Multi-Target TrackingCode1
Scene Map-based Prompt Tuning for Navigation Instruction Generation—0
TADFormer: Task-Adaptive Dynamic TransFormer for Efficient Multi-Task Learning—0
Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding—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