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 1001–1010 of 1723 papers

TitleStatusHype
Dense Supervision Propagation for Weakly Supervised Semantic Segmentation on 3D Point Clouds—0
Object Recognition System on a Tactile Device for Visually Impaired—0
Object segmentation in depth maps with one user click and a synthetically trained fully convolutional network—0
ObjVariantEnsemble: Advancing Point Cloud LLM Evaluation in Challenging Scenes with Subtly Distinguished Objects—0
Occam's LGS: A Simple Approach for Language Gaussian Splatting—0
OccLE: Label-Efficient 3D Semantic Occupancy Prediction—0
Dense RGB-D semantic mapping with Pixel-Voxel neural network—0
Dense Multimodal Alignment for Open-Vocabulary 3D Scene Understanding—0
Occlusion Boundary Detection via Deep Exploration of Context—0
Deep Structured Scene Parsing by Learning with Image Descriptions—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