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 441–450 of 1723 papers

TitleStatusHype
3D Question Answering for City Scene Understanding—0
Augmented Efficiency: Reducing Memory Footprint and Accelerating Inference for 3D Semantic Segmentation through Hybrid Vision—0
InLUT3D: Challenging real indoor dataset for point cloud analysis—0
VideoGameBunny: Towards vision assistants for video games—0
A New Lightweight Hybrid Graph Convolutional Neural Network -- CNN Scheme for Scene Classification using Object Detection InferenceCode0
GaussianBeV: 3D Gaussian Representation meets Perception Models for BeV Segmentation—0
MC-PanDA: Mask Confidence for Panoptic Domain AdaptationCode0
OpenSU3D: Open World 3D Scene Understanding using Foundation Models—0
Open Vocabulary 3D Scene Understanding via Geometry Guided Self-Distillation—0
Training-Free Model Merging for Multi-target Domain Adaptation—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