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 1401–1410 of 1723 papers

TitleStatusHype
Single Image 3D Without a Single 3D Image—0
Single Image Depth Estimation: An Overview—0
Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning—0
3D-Grounded Vision-Language Framework for Robotic Task Planning: Automated Prompt Synthesis and Supervised Reasoning—0
AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy—0
You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects—0
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture—0
Augmented Efficiency: Reducing Memory Footprint and Accelerating Inference for 3D Semantic Segmentation through Hybrid Vision—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
SkyScenes: A Synthetic Dataset for Aerial 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