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 681–690 of 1723 papers

TitleStatusHype
Leverage Cross-Attention for End-to-End Open-Vocabulary Panoptic Reconstruction—0
TADFormer: Task-Adaptive Dynamic TransFormer for Efficient Multi-Task Learning—0
Scene Map-based Prompt Tuning for Navigation Instruction Generation—0
Vision-Language Embodiment for Monocular Depth Estimation—0
Beyond Human Perception: Understanding Multi-Object World from Monocular ViewCode0
AVQACL: A Novel Benchmark for Audio-Visual Question Answering Continual LearningCode0
HUSH: Holistic Panoramic 3D Scene Understanding using Spherical Harmonics—0
Object-aware Sound Source Localization via Audio-Visual Scene UnderstandingCode0
GroundingFace: Fine-grained Face Understanding via Pixel Grounding Multimodal Large Language Model—0
3D-MVP: 3D Multiview Pretraining for Manipulation—0
Show:102550
← PrevPage 69 of 173Next →
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