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 871–880 of 1723 papers

TitleStatusHype
A Continuous Occlusion Model for Road Scene Understanding—0
Dr. Splat: Directly Referring 3D Gaussian Splatting via Direct Language Embedding Registration—0
Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs—0
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds—0
Mining Conditional Part Semantics with Occluded Extrapolation for Human-Object Interaction Detection—0
Content Adaptive Front End For Audio Classification—0
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models—0
MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation—0
Unified Representation Space for 3D Visual Grounding—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